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README.md

@@ -1,3 +1,407 @@
----
-license: llama3
----
+---
+language:
+- en
+- it
+license: llama3
+library_name: transformers
+tags:
+- facebook
+- meta
+- pythorch
+- llama
+- llama-3
+- llamantino
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+datasets:
+- gsarti/clean_mc4_it
+- Chat-Error/wizard_alpaca_dolly_orca
+- mlabonne/orpo-dpo-mix-40k
+metrics:
+- accuracy
+model_creator: Marco Polignano - SWAP Research Group
+pipeline_tag: text-generation
+model-index:
+- name: LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 74.57
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 92.75
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 66.85
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 75.93
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 82.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 58.61
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+---
+---
+
+# OpenVINO IR model with int4 quantization of LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+
+Model definition for LocalAI:
+```yaml
+name: anita-llama3
+backend: transformers
+parameters:
+  model: fakezeta/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-ov-int4
+context_size: 8192
+type: OVModelForCausalLM
+template:
+  use_tokenizer_template: true
+```
+
+To run the model directly with LocalAI:
+```
+local-ai run huggingface://fakezeta/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-ov-int4/model.yaml
+```
+
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/5df8bb21da6d0311fd3d540f/xL6Ax1I34qfC4VPKEFA6Z.png" alt="llamantino3_anita" border="0" width="800px">
+aaa
+<hr>
+<!--<img src="https://i.ibb.co/6mHSRm3/llamantino53.jpg" width="200"/>-->
+<h3><i>"Built with <b>Meta Llama 3</b>".</i></i></h3>
+<p style="text-align:justify;"><b>LLaMAntino-3-ANITA-8B-Inst-DPO-ITA</b> is a model of the <a href="https://huggingface.co/swap-uniba"><b>LLaMAntino</b></a> - <i>Large Language Models family</i>.
+The model is an instruction-tuned version of <a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct"><b>Meta-Llama-3-8b-instruct</b></a> (a fine-tuned <b>LLaMA 3 model</b>).
+This model version aims to be the a <b>Multilingual Model</b> 🏁  (EN 🇺🇸 + ITA🇮🇹) to further fine-tuning on Specific Tasks in Italian.</p>
+
+
+The 🌟**ANITA project**🌟 *(**A**dvanced **N**atural-based interaction for the **ITA**lian language)*
+wants to provide Italian NLP researchers with an improved model for the Italian Language 🇮🇹 use cases.<br>
+
+<hr>
+
+**Live DEMO:** [https://chat.llamantino.it/](https://chat.llamantino.it/)<br>
+*It works only with Italian connection.*
+
+<hr>
+
+## Model Details
+*Last Update: 10/05/2024*<br>
+
+<a href="https://github.com/marcopoli/LLaMAntino-3-ANITA"><img src="https://github.githubassets.com/assets/GitHub-Logo-ee398b662d42.png" width="150"> https://github.com/marcopoli/LLaMAntino-3-ANITA</a><br>
+
+| Model | HF   | GGUF   | EXL2   |
+|-------|-------|-------|-------|
+| *swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA* | [Link](https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA) | [Link](https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA_GGUF) | [Link](https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA_EXL2) |
+
+<hr>
+
+## Specifications
+
+- **Model developers**: <br><a href="https://marcopoli.github.io/">Ph.D. Marco Polignano</a> - University of Bari Aldo Moro, Italy <br> <a href="https://huggingface.co/swap-uniba">SWAP Research Group</a> <br>
+- **Variations**: The model release has been **supervised fine-tuning (SFT)** using **QLoRA** 4bit, on instruction-based datasets. **DPO** approach over the *mlabonne/orpo-dpo-mix-40k* dataset is used to align with human preferences for helpfulness and safety.
+- **Input**: Models input text only.
+- **Language**: Multilingual 🏁 + Italian 🇮🇹
+- **Output**: Models generate text and code only.
+- **Model Architecture**: *Llama 3 architecture*.
+- **Context length**: 8K, 8192.
+- **Library Used**: [Unsloth](https://unsloth.ai/)
+<hr>
+
+## Playground
+
+To use the model directly, there are many ways to get started, choose one of the following ways to experience it.
+
+### Prompt Template
+```
+<|start_header_id|>system<|end_header_id|>
+
+{ SYS Prompt }<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+{ USER Prompt }<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+{ ASSIST Prompt }<|eot_id|>
+````
+
+### Transformers
+
+For direct use with `transformers`, you can easily get started with the following steps.
+
+- Firstly, you need to install transformers via the command below with `pip`.
+
+  ```bash
+  pip install -U transformers trl peft accelerate bitsandbytes
+  ```
+
+- Right now, you can start using the model directly.
+
+  ```python
+  import torch
+  from transformers import (
+      AutoModelForCausalLM,
+      AutoTokenizer,
+  )
+  
+  base_model = "swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA"
+  model = AutoModelForCausalLM.from_pretrained(
+      base_model,
+      torch_dtype=torch.bfloat16,
+      device_map="auto",
+  )
+  tokenizer = AutoTokenizer.from_pretrained(base_model)
+  
+  sys = "Sei un an assistente AI per la lingua Italiana di nome LLaMAntino-3 ANITA " \
+      "(Advanced Natural-based interaction for the ITAlian language)." \
+      " Rispondi nella lingua usata per la domanda in modo chiaro, semplice ed esaustivo."
+  
+  messages = [
+      {"role": "system", "content": sys},
+      {"role": "user", "content": "Chi è Carlo Magno?"}
+  ]
+
+  #Method 1
+  prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+  inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
+  for k,v in inputs.items():
+      inputs[k] = v.cuda()
+  outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, top_p=0.9, temperature=0.6)
+  results = tokenizer.batch_decode(outputs)[0]
+  print(results)
+
+  #Method 2
+  import transformers
+  pipe = transformers.pipeline(
+      model=model,
+      tokenizer=tokenizer,
+      return_full_text=False, # langchain expects the full text
+      task='text-generation',
+      max_new_tokens=512, # max number of tokens to generate in the output
+      temperature=0.6,  #temperature for more or less creative answers
+      do_sample=True,
+      top_p=0.9,
+  )
+
+  sequences = pipe(messages)
+  for seq in sequences:
+      print(f"{seq['generated_text']}")
+  
+  ```
+
+- Additionally, you can also use a model with **4bit quantization** to reduce the required resources at least. You can start with the code below.
+
+  ```python
+  import torch
+  from transformers import (
+      AutoModelForCausalLM,
+      AutoTokenizer,
+      BitsAndBytesConfig,
+  )
+
+  base_model = "swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA"
+  bnb_config = BitsAndBytesConfig(
+      load_in_4bit=True,
+      bnb_4bit_quant_type="nf4",
+      bnb_4bit_compute_dtype=torch.bfloat16,
+      bnb_4bit_use_double_quant=False,
+  )
+  model = AutoModelForCausalLM.from_pretrained(
+      base_model,
+      quantization_config=bnb_config,
+      device_map="auto",
+  )
+  tokenizer = AutoTokenizer.from_pretrained(base_model)
+
+  sys = "Sei un an assistente AI per la lingua Italiana di nome LLaMAntino-3 ANITA " \
+      "(Advanced Natural-based interaction for the ITAlian language)." \
+      " Rispondi nella lingua usata per la domanda in modo chiaro, semplice ed esaustivo."
+  
+  messages = [
+      {"role": "system", "content": sys},
+      {"role": "user", "content": "Chi è Carlo Magno?"}
+  ]
+
+  #Method 1
+  prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+  inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
+  for k,v in inputs.items():
+      inputs[k] = v.cuda()
+  outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, top_p=0.9, temperature=0.6)
+  results = tokenizer.batch_decode(outputs)[0]
+  print(results)
+
+  #Method 2
+  import transformers
+  pipe = transformers.pipeline(
+      model=model,
+      tokenizer=tokenizer,
+      return_full_text=False, # langchain expects the full text
+      task='text-generation',
+      max_new_tokens=512, # max number of tokens to generate in the output
+      temperature=0.6,  #temperature for more or less creative answers
+      do_sample=True,
+      top_p=0.9,
+  )
+
+  sequences = pipe(messages)
+  for seq in sequences:
+      print(f"{seq['generated_text']}")
+
+  ```
+
+<hr>
+
+## Evaluation
+
+**Open LLM Leaderboard:**
+
+Evaluated with lm-evaluation-benchmark-harness for the [**Open Italian LLMs Leaderboard**](https://huggingface.co/spaces/FinancialSupport/open_ita_llm_leaderboard)
+```
+   lm_eval --model hf --model_args pretrained=HUGGINGFACE_MODEL_ID  --tasks hellaswag_it,arc_it  --device cuda:0 --batch_size auto:2
+   lm_eval --model hf --model_args pretrained=HUGGINGFACE_MODEL_ID  --tasks m_mmlu_it --num_fewshot 5  --device cuda:0 --batch_size auto:2 
+```
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | **0.6160**  |
+| Arc_IT         | 0.5714 |
+| Hellaswag_IT    | 0.7093 |
+| MMLU_IT          | 0.5672 |
+
+<hr>
+
+## Unsloth
+
+<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made with unsloth.png" width="200px" align="center" />
+
+[Unsloth](https://unsloth.ai), a great tool that helps us easily develop products, at a lower cost than expected.
+
+## Citation instructions
+```bibtex
+@misc{polignano2024advanced,
+      title={Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA}, 
+      author={Marco Polignano and Pierpaolo Basile and Giovanni Semeraro},
+      year={2024},
+      eprint={2405.07101},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+```bibtex
+@misc{basile2023llamantino,
+      title={LLaMAntino: LLaMA 2 Models for Effective Text Generation in Italian Language}, 
+      author={Pierpaolo Basile and Elio Musacchio and Marco Polignano and Lucia Siciliani and Giuseppe Fiameni and Giovanni Semeraro},
+      year={2023},
+      eprint={2312.09993},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+```bibtex
+@article{llama3modelcard,
+  title={Llama 3 Model Card},
+  author={AI@Meta},
+  year={2024},
+  url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
+}
+```
+
+# Acknowledgments
+We acknowledge the support of the PNRR project [FAIR - Future AI Research (PE00000013)](https://fondazione-fair.it/en/foundation/), Spoke 6 - Symbiotic AI (CUP H97G22000210007) under the NRRP MUR program funded by the NextGenerationEU.
+Models are built on the Leonardo supercomputer with the support of CINECA-Italian Super Computing Resource Allocation, class C project IscrC\_Pro\_MRS (HP10CQO70G).
+<img src="https://wiki.u-gov.it/confluence/download/attachments/49842317/image2022-6-21_11-11-44.png?version=1&modificationDate=1655802705000&api=v2" width="600px">
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_swap-uniba__LLaMAntino-3-ANITA-8B-Inst-DPO-ITA)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |75.12|
+|AI2 Reasoning Challenge (25-Shot)|74.57|
+|HellaSwag (10-Shot)              |92.75|
+|MMLU (5-Shot)                    |66.85|
+|TruthfulQA (0-shot)              |75.93|
+|Winogrande (5-shot)              |82.00|
+|GSM8k (5-shot)                   |58.61|
+

config.json

@@ -0,0 +1,28 @@
+{
+  "_name_or_path": "swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.41.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

@@ -0,0 +1,12 @@
+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128009
+  ],
+  "max_length": 8192,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.41.2"
+}

model.yaml

@@ -0,0 +1,8 @@
+name: anita-llama3
+backend: transformers
+parameters:
+  model: fakezeta/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-ov-int4
+context_size: 8192
+type: OVModelForCausalLM
+template:
+  use_tokenizer_template: true

openvino_detokenizer.bin

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+oid sha256:8d1c1a9143e35a173f499bcbc34c5aba3382a3ddad209dd8f365aceaa22ba211
+size 1586526

openvino_detokenizer.xml

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+<net name="detokenizer" version="11">
+	<layers>
+		<layer id="0" name="Parameter_228891" type="Parameter" version="opset1">
+			<data shape="?,?" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="Parameter_228891">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="Convert_228907" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>-1</dim>
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+				</port>
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+		</layer>
+		<layer id="2" name="Constant_228794" type="Const" version="opset1">
+			<data element_type="u8" shape="1586477" offset="0" size="1586477" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>1586477</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="StringTensorUnpack_228795" type="StringTensorUnpack" version="extension">
+			<data mode="begins_ends" />
+			<input>
+				<port id="0" precision="U8">
+					<dim>1586477</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
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+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="U8">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="VocabDecoder_228892" type="VocabDecoder" version="extension">
+			<data skip_tokens="128000, 128001, 128002, 128003, 128004, 128005, 128006, 128007, 128008, 128009, 128010, 128011, 128012, 128013, 128014, 128015, 128016, 128017, 128018, 128019, 128020, 128021, 128022, 128023, 128024, 128025, 128026, 128027, 128028, 128029, 128030, 128031, 128032, 128033, 128034, 128035, 128036, 128037, 128038, 128039, 128040, 128041, 128042, 128043, 128044, 128045, 128046, 128047, 128048, 128049, 128050, 128051, 128052, 128053, 128054, 128055, 128056, 128057, 128058, 128059, 128060, 128061, 128062, 128063, 128064, 128065, 128066, 128067, 128068, 128069, 128070, 128071, 128072, 128073, 128074, 128075, 128076, 128077, 128078, 128079, 128080, 128081, 128082, 128083, 128084, 128085, 128086, 128087, 128088, 128089, 128090, 128091, 128092, 128093, 128094, 128095, 128096, 128097, 128098, 128099, 128100, 128101, 128102, 128103, 128104, 128105, 128106, 128107, 128108, 128109, 128110, 128111, 128112, 128113, 128114, 128115, 128116, 128117, 128118, 128119, 128120, 128121, 128122, 128123, 128124, 128125, 128126, 128127, 128128, 128129, 128130, 128131, 128132, 128133, 128134, 128135, 128136, 128137, 128138, 128139, 128140, 128141, 128142, 128143, 128144, 128145, 128146, 128147, 128148, 128149, 128150, 128151, 128152, 128153, 128154, 128155, 128156, 128157, 128158, 128159, 128160, 128161, 128162, 128163, 128164, 128165, 128166, 128167, 128168, 128169, 128170, 128171, 128172, 128173, 128174, 128175, 128176, 128177, 128178, 128179, 128180, 128181, 128182, 128183, 128184, 128185, 128186, 128187, 128188, 128189, 128190, 128191, 128192, 128193, 128194, 128195, 128196, 128197, 128198, 128199, 128200, 128201, 128202, 128203, 128204, 128205, 128206, 128207, 128208, 128209, 128210, 128211, 128212, 128213, 128214, 128215, 128216, 128217, 128218, 128219, 128220, 128221, 128222, 128223, 128224, 128225, 128226, 128227, 128228, 128229, 128230, 128231, 128232, 128233, 128234, 128235, 128236, 128237, 128238, 128239, 128240, 128241, 128242, 128243, 128244, 128245, 128246, 128247, 128248, 128249, 128250, 128251, 128252, 128253, 128254, 128255" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
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+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="U8">
+					<dim>-1</dim>
+				</port>
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+			<data global_replace="true" />
+			<input>
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openvino_tokenizer.bin

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openvino_tokenizer.xml

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+			<input>
+				<port id="0" precision="I64" />
+				<port id="1" precision="I64" />
+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="34" name="Constant_228807" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="8" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="35" name="Constant_228808" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="8" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="36" name="Add_228809" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I64" />
+				<port id="1" precision="I64" />
+			</input>
+			<output>
+				<port id="2" precision="I64" />
+			</output>
+		</layer>
+		<layer id="37" name="Constant_228810" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="8" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="38" name="Range_228811" type="Range" version="opset4">
+			<data output_type="i32" />
+			<input>
+				<port id="0" precision="I64" />
+				<port id="1" precision="I64" />
+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="39" name="BytesToChars_228873" type="BytesToChars" version="extension">
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="4" precision="U8">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="5" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="6" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="7" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="8" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="9" precision="U8">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="40" name="Constant_228877" type="Const" version="opset1">
+			<data element_type="i32" shape="256" offset="5688105" size="1024" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="41" name="BPETokenizer_228878" type="BPETokenizer" version="extension">
+			<data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="4" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="5" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="6" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="7" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="8" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="9" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="10" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="11" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="12" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="13" precision="U8">
+					<dim>-1</dim>
+				</port>
+				<port id="14" precision="I32">
+					<dim>256</dim>
+				</port>
+			</input>
+			<output>
+				<port id="15" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="16" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="17" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="42" name="Subtract_228879" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="43" name="Constant_228880" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="5689129" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="44" name="Minimum_228881" type="Minimum" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="45" name="Add_228882" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="46" name="Subtract_228883" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="47" name="Constant_228884" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="5689133" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="48" name="ReduceMax_228885" type="ReduceMax" version="opset1">
+			<data keep_dims="false" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" />
+			</output>
+		</layer>
+		<layer id="49" name="Constant_228886" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="5689133" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="50" name="RaggedToDense_228887" type="RaggedToDense" version="extension">
+			<data pad_right="true" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="3" precision="I32" />
+				<port id="4" precision="I32" />
+			</input>
+			<output>
+				<port id="5" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+				<port id="6" precision="BOOL">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="51" name="Convert_228888" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="BOOL">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="52" name="Convert_228888" type="Convert" version="opset1">
+			<data destination_type="i64" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" names="attention_mask">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="54" name="RaggedToDense_228887.0" type="Convert" version="opset1">
+			<data destination_type="i64" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" names="input_ids">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="55" name="Result_228889" type="Result" version="opset1">
+			<input>
+				<port id="0" precision="I64">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+		</layer>
+		<layer id="53" name="Result_228890" type="Result" version="opset1">
+			<input>
+				<port id="0" precision="I64">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+		</layer>
+	</layers>
+	<edges>
+		<edge from-layer="0" from-port="0" to-layer="2" to-port="0" />
+		<edge from-layer="1" from-port="0" to-layer="8" to-port="0" />
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+		<edge from-layer="39" from-port="8" to-layer="41" to-port="12" />
+		<edge from-layer="39" from-port="9" to-layer="41" to-port="13" />
+		<edge from-layer="40" from-port="0" to-layer="41" to-port="14" />
+		<edge from-layer="41" from-port="15" to-layer="45" to-port="0" />
+		<edge from-layer="41" from-port="17" to-layer="50" to-port="2" />
+		<edge from-layer="41" from-port="15" to-layer="50" to-port="0" />
+		<edge from-layer="41" from-port="15" to-layer="46" to-port="1" />
+		<edge from-layer="41" from-port="15" to-layer="42" to-port="1" />
+		<edge from-layer="41" from-port="16" to-layer="42" to-port="0" />
+		<edge from-layer="42" from-port="2" to-layer="44" to-port="0" />
+		<edge from-layer="43" from-port="0" to-layer="44" to-port="1" />
+		<edge from-layer="44" from-port="2" to-layer="45" to-port="1" />
+		<edge from-layer="45" from-port="2" to-layer="46" to-port="0" />
+		<edge from-layer="45" from-port="2" to-layer="50" to-port="1" />
+		<edge from-layer="46" from-port="2" to-layer="48" to-port="0" />
+		<edge from-layer="47" from-port="0" to-layer="48" to-port="1" />
+		<edge from-layer="48" from-port="2" to-layer="50" to-port="3" />
+		<edge from-layer="49" from-port="0" to-layer="50" to-port="4" />
+		<edge from-layer="50" from-port="6" to-layer="51" to-port="0" />
+		<edge from-layer="50" from-port="5" to-layer="54" to-port="0" />
+		<edge from-layer="51" from-port="1" to-layer="52" to-port="0" />
+		<edge from-layer="52" from-port="1" to-layer="53" to-port="0" />
+		<edge from-layer="54" from-port="1" to-layer="55" to-port="0" />
+	</edges>
+	<rt_info>
+		<eos_token_id value="128009" />
+	</rt_info>
+</net>

special_tokens_map.json

@@ -0,0 +1,16 @@
+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,2062 @@
+{
+  "added_tokens_decoder": {
+    "128000": {
+      "content": "<|begin_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128001": {
+      "content": "<|end_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128002": {
+      "content": "<|reserved_special_token_0|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128003": {
+      "content": "<|reserved_special_token_1|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128004": {
+      "content": "<|reserved_special_token_2|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128005": {
+      "content": "<|reserved_special_token_3|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128006": {
+      "content": "<|start_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128007": {
+      "content": "<|end_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128008": {
+      "content": "<|reserved_special_token_4|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+      "single_word": false,
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+      "single_word": false,
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+    },
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+    },
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+    },
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+      "single_word": false,
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+    },
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+    },
+    "128221": {
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+    },
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+    },
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+      "single_word": false,
+      "special": true
+    },
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+      "content": "<|reserved_special_token_228|>",
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 1000000000000000019884624838656,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}