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Browse files- README.md +96 -0
- added_tokens.json +57 -0
- config.json +37 -0
- generation_config.json +7 -0
- model.safetensors.index.json +298 -0
- output.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +486 -0
README.md
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---
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license: apache-2.0
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datasets:
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- OpenAssistant/oasst1
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- zetavg/ShareGPT-Processed
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- augmxnt/ultra-orca-boros-en-ja-v1
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language:
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- ja
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- en
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---
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64c8a2e01c25d2c581a381c1/9CbN4lDGU42c-7DmK_mGM.png" alt="drawing" width="600"/>
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</p>
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# Evaluation
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/dYASMWRzqKjc-pZ8pDE7x.png)
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# How to use
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### Hugggingface
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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tokenizer = AutoTokenizer.from_pretrained("lightblue/karasu-7B-chat-plus")
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model = AutoModelForCausalLM.from_pretrained("lightblue/karasu-7B-chat-plus", torch_dtype=torch.bfloat16, device_map="auto")
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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messages = [{"role": "system", "content": "あなたはAIアシスタントです。"}]
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messages.append({"role": "user", "content": "イギリスの首相は誰ですか?"})
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prompt = tokenizer.apply_chat_template(conversation=messages, add_generation_prompt=True, tokenize=False)
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pipe(prompt, max_new_tokens=100, do_sample=False, temperature=0.0, return_full_text=False)
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```
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### VLLM
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```python
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from vllm import LLM, SamplingParams
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sampling_params = SamplingParams(temperature=0.0, max_tokens=100)
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llm = LLM(model="lightblue/karasu-7B-chat-plus")
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messages = [{"role": "system", "content": "あなたはAIアシスタントです。"}]
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messages.append({"role": "user", "content": "イギリスの首相は誰ですか?"})
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prompt = llm.llm_engine.tokenizer.apply_chat_template(conversation=messages, add_generation_prompt=True, tokenize=False)
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prompts = [prompt]
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outputs = llm.generate(prompts, sampling_params)
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for output in outputs:
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prompt = output.prompt
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generated_text = output.outputs[0].text
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print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
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```
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# Base checkpoint
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[lightblue/karasu-7B](https://huggingface.co/lightblue/karasu-7B)
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# Training datasets (total ~7B)
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* Lightblue's suite of Kujira datasets (unreleased)
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* Lightblue's own question-based datasets (unreleased)
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* Lightblue's own category-based datasets (unreleased)
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* [OASST](https://huggingface.co/datasets/OpenAssistant/oasst1) (Japanese chats only)
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* [ShareGPT](https://huggingface.co/datasets/zetavg/ShareGPT-Processed) (Japanese chats only)
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* [augmxnt/ultra-orca-boros-en-ja-v1](https://huggingface.co/datasets/augmxnt/ultra-orca-boros-en-ja-v1) (['airoboros', 'slimorca', 'ultrafeedback', 'airoboros_ja_new'] only)
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# Developed by
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<a href="https://www.lightblue-tech.com">
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<img src="https://www.lightblue-tech.com/wp-content/uploads/2023/08/color_%E6%A8%AA%E5%9E%8B-1536x469.png" alt="Lightblue technology logo" width="400"/>
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</a>
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### Engineers
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Peter Devine
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Sho Higuchi
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### Advisors
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Yuuki Yamanaka
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Atom Sonoda
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### Project manager
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Shunichi Taniguchi
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### Dataset evaluator
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Renju Aoki
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added_tokens.json
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{
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"<|extra_44|>": 32044,
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"<|extra_45|>": 32045,
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"<|extra_46|>": 32046,
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"<|extra_47|>": 32047,
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"<|extra_48|>": 32048,
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"<|extra_49|>": 32049,
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"<|extra_4|>": 32004,
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"<|extra_50|>": 32050,
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"<|extra_51|>": 32051,
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"<|extra_52|>": 32052,
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"<|extra_53|>": 32053,
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"<|extra_8|>": 32008,
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"<|extra_9|>": 32009
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}
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config.json
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{
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"_name_or_path": "/workspace/multihumpbackplus/pretraining/cat_wiki_kuj_aug_oas_shar_shisa",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.36.0.dev0",
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"use_cache": false,
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"vocab_size": 120128,
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"quantization_config": {
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"quant_method": "exl2",
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"version": "0.0.19",
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"bits": 4.0,
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"head_bits": 6,
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"calibration": {
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"rows": 100,
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"length": 2048,
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"dataset": "(default)"
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}
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}
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.36.0.dev0",
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"use_cache": false
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}
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model.safetensors.index.json
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{
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"metadata": {
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"total_size": 15927353344
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},
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"weight_map": {
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458 |
+
"single_word": false,
|
459 |
+
"special": false
|
460 |
+
},
|
461 |
+
"32054": {
|
462 |
+
"content": "<|extra_54|>",
|
463 |
+
"lstrip": false,
|
464 |
+
"normalized": false,
|
465 |
+
"rstrip": false,
|
466 |
+
"single_word": false,
|
467 |
+
"special": false
|
468 |
+
}
|
469 |
+
},
|
470 |
+
"additional_special_tokens": [],
|
471 |
+
"bos_token": "<s>",
|
472 |
+
"chat_template": "{%- for idx in range(0, messages|length) -%}\n{%- if messages[idx]['role'] == 'user' -%}\n{%- if idx > 1 -%}\n{{- bos_token + '[INST] ' + messages[idx]['content'] + ' [/INST]' -}}\n{%- else -%}\n{{- messages[idx]['content'] + ' [/INST]' -}}\n{%- endif -%}\n{% elif messages[idx]['role'] == 'system' %}\n{{- bos_token + '[INST] <<SYS>>\\n' + messages[idx]['content'] + '\\n<</SYS>>\\n\\n' -}}\n{%- elif messages[idx]['role'] == 'assistant' -%}\n{{- ' ' + messages[idx]['content'] + ' ' + eos_token -}}\n{% endif %}\n{% endfor %}\n",
|
473 |
+
"clean_up_tokenization_spaces": false,
|
474 |
+
"eos_token": "</s>",
|
475 |
+
"legacy": true,
|
476 |
+
"model_max_length": 1000000000000000019884624838656,
|
477 |
+
"pad_token": "<unk>",
|
478 |
+
"padding_side": "right",
|
479 |
+
"sp_model_kwargs": {},
|
480 |
+
"spaces_between_special_tokens": false,
|
481 |
+
"tokenizer_class": "LlamaTokenizer",
|
482 |
+
"trust_remote_code": false,
|
483 |
+
"unk_token": "<unk>",
|
484 |
+
"use_default_system_prompt": false,
|
485 |
+
"use_fast": true
|
486 |
+
}
|