faced65r64
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Upload 9 files
Browse files- Modelfile +12 -0
- README.md +46 -0
- adapter_config.json +34 -0
- adapter_model.safetensors +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +0 -0
- training_args.bin +3 -0
- training_params.json +49 -0
Modelfile
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FROM .
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TEMPLATE """{{ if .System }}<|im_start|>system
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{{ .System }}<|im_end|>{{ end }}
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<|im_start|>user
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{{ .Prompt }}<|im_end|>
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<|im_start|>assistant
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"""
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PARAMETER stop <|start_header_id|>
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PARAMETER stop <|end_header_id|>
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PARAMETER stop <|eot_id|>
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README.md
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---
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tags:
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- autotrain
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- text-generation-inference
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- text-generation
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- peft
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library_name: transformers
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base_model: mistralai/Mistral-Nemo-Instruct-2407
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widget:
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- messages:
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- role: user
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content: What is your favorite condiment?
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license: other
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---
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# Model Trained Using AutoTrain
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This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
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# Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = "PATH_TO_THIS_REPO"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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device_map="auto",
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torch_dtype='auto'
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).eval()
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# Prompt content: "hi"
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messages = [
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{"role": "user", "content": "hi"}
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]
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input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
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output_ids = model.generate(input_ids.to('cuda'))
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response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
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# Model response: "Hello! How can I assist you today?"
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print(response)
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```
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "mistralai/Mistral-Nemo-Instruct-2407",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"q_proj",
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"down_proj",
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"v_proj",
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"gate_proj",
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"k_proj",
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"up_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c4bf112506f6527f157bef04f5d9cfb0b29f407804f0fc11300ecefe47a14075
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size 228140600
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "</s>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:5f1f98676ac91a059439954b2b75bc23a12a1f323cb01041fd27613c2239a9c0
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size 5432
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training_params.json
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{
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"model": "mistralai/Mistral-Nemo-Instruct-2407",
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"project_name": "my-autotrain-llm",
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"data_path": "my-autotrain-llm/autotrain-data",
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"train_split": "train",
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"valid_split": null,
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"add_eos_token": true,
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"block_size": 1024,
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"model_max_length": 2048,
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"padding": "right",
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"trainer": "sft",
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"use_flash_attention_2": false,
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"log": "tensorboard",
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"disable_gradient_checkpointing": false,
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"logging_steps": -1,
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"eval_strategy": "epoch",
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"save_total_limit": 1,
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"auto_find_batch_size": false,
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"mixed_precision": "none",
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"lr": 0.0002,
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"epochs": 1,
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"batch_size": 1,
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"warmup_ratio": 0.1,
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"gradient_accumulation": 4,
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"optimizer": "adamw_torch",
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"scheduler": "linear",
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"weight_decay": 0.01,
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"max_grad_norm": 1.0,
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"seed": 42,
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"chat_template": null,
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"quantization": "int4",
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"target_modules": "all-linear",
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"merge_adapter": false,
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"peft": true,
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"lora_r": 16,
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"model_ref": null,
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"dpo_beta": 0.1,
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"max_prompt_length": 128,
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"max_completion_length": null,
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"prompt_text_column": "autotrain_prompt",
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"text_column": "autotrain_text",
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"rejected_text_column": "autotrain_rejected_text",
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"push_to_hub": false,
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"username": "face",
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"token": null,
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"unsloth": true
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}
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