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Model: Weyaxi/Newton-7B Source: Original Platform
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README.md
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README.md
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---
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license: other
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tags:
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- axolotl
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- finetune
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- qlora
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base_model: openchat/openchat-3.5-0106
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datasets:
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- hendrycks/competition_math
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- allenai/ai2_arc
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- camel-ai/physics
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- camel-ai/chemistry
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- camel-ai/biology
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- camel-ai/math
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- STEM-AI-mtl/Electrical-engineering
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- openbookqa
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- piqa
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- metaeval/reclor
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- mandyyyyii/scibench
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- derek-thomas/ScienceQA
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- sciq
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- TIGER-Lab/ScienceEval
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---
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# 🔬👩🔬 Newton-7B
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This model is a fine-tuned version of [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) on datasets related to science.
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This model is fine-tuned using [QLoRa](https://arxiv.org/abs/2305.14314) and [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl).
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This model's training was sponsored by [sablo.ai](https://sablo.ai).
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<details><summary>See axolotl config</summary>
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axolotl version: `0.3.0`
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```yaml
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base_model: openchat/openchat-3.5-0106
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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datasets:
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- path: merged_all.json
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type:
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field_instruction: instruction
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field_output: output
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format: "GPT4 Correct User: {instruction}<|end_of_turn|>GPT4 Correct Assistant:"
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no_input_format: "GPT4 Correct User: {instruction}<|end_of_turn|>GPT4 Correct Assistant:"
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.01 # not sure
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output_dir: ./newton
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adapter: qlora
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lora_model_dir:
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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lora_r: 128
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lora_alpha: 64
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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lora_modules_to_save:
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- embed_tokens
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- lm_head
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wandb_project: huggingface
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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hub_model_id: Weyaxi/newton-lora
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save_safetensors: true
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# change #
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gradient_accumulation_steps: 12
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micro_batch_size: 6
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num_epochs: 2
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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# change #
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train_on_inputs: false
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group_by_length: false
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bf16: true
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fp16: false
|
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tf32: false
|
||||
|
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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|
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warmup_steps: 10 # not sure
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saves_per_epoch: 2
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|
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evals_per_epoch: 4
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eval_table_size:
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eval_table_max_new_tokens: 128
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|
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debug:
|
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deepspeed:
|
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weight_decay: 0.1 # not sure
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fsdp:
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fsdp_config:
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special_tokens:
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bos_token: "<s>"
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eos_token: "</s>"
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unk_token: "<unk>"
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tokens:
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- "<|end_of_turn|>"
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- "<|pad_0|>"
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```
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</details><br>
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# 📊 Datasets
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You can find the dataset I used and the work I am doing with this datasets here:
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https://huggingface.co/datasets/Weyaxi/sci-datasets
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Following datasets were used in this model:
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- 📐 [MATH](https://huggingface.co/datasets/hendrycks/competition_math)
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- 🧠 [ARC](https://huggingface.co/datasets/allenai/ai2_arc) (Note: Only **train** part)
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- 🧲 [camel-ai/physics](https://huggingface.co/datasets/camel-ai/physics)
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- ⚗️ [camel-ai/chemistry](https://huggingface.co/datasets/camel-ai/chemistry)
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- 🦠 [camel-ai/biology](https://huggingface.co/datasets/camel-ai/biology)
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- 📊 [camel-ai/math](https://huggingface.co/datasets/camel-ai/math)
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- ⚡ [STEM-AI-mtl/Electrical-engineering](https://huggingface.co/datasets/STEM-AI-mtl/Electrical-engineering)
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|
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- 📚 [openbookqa](https://huggingface.co/datasets/openbookqa)
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|
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- 🧠 [piqa](https://huggingface.co/datasets/piqa)
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|
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- 🎨 [reclor](https://huggingface.co/datasets/metaeval/reclor)
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|
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- 🔬 [scibench](https://github.com/mandyyyyii/scibench)
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|
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- 🧪 [ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA)
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|
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- 🧬 [sciq](https://huggingface.co/datasets/sciq)
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|
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- 📝 [ScienceEval](https://huggingface.co/datasets/TIGER-Lab/ScienceEval)
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## 🛠️ Multiple Choice Question & Answer Datasets Conversion Progress
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I used [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) to generate a reasonable and logical answer by providing it with the question and the answer key.
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I used the [Together AI](https://www.together.ai) API for this task.
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The following datasets are converted using this method:
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|
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- 🧠 [ARC](https://huggingface.co/datasets/allenai/ai2_arc) (Note: Only **train** part)
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|
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- 📚 [openbookqa](https://huggingface.co/datasets/openbookqa)
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||||
|
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- 🎨 [reclor](https://huggingface.co/datasets/metaeval/reclor)
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|
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- 🧬 [sciq](https://huggingface.co/datasets/sciq)
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# 💬 Prompt Template
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You can use this prompt template while using the model:
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### GPT4 Correct [(Openchat)](https://huggingface.co/openchat/openchat-3.5-0106#conversation-templates)
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```
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GPT4 Correct User: {user}<|end_of_turn|>GPT4 Correct Assistant: {asistant}<|end_of_turn|>GPT4 Correct User: {user}<|end_of_turn|>GPT4 Correct Assistant:
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```
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You can also utilize the chat template method from the tokenizer config like here:
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```python
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messages = [
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{"role": "user", "content": "Hello"},
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{"role": "assistant", "content": "Hi"},
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{"role": "user", "content": "How are you today?"}
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]
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tokens = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
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```
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# 🤝 Acknowledgments
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Thanks to [openchat](https://huggingface.co/openchat) team for fine-tuning an excellent model that I used as a base model.
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Thanks to [@jondurbin](https://huggingface.co/jondurbin) for reformatting codes for some datasets: [bagel/data_sources](https://github.com/jondurbin/bagel/tree/main/bagel/data_sources)
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Thanks to [Together AI](https://www.together.ai) for providing everyone with free credits, which I used to generate a dataset in multiple choice to explanations format.
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Thanks to [Tim Dettmers](https://huggingface.co/timdettmers) for his excellent [QLoRA](https://arxiv.org/abs/2305.14314) work.
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Thanks to all the dataset authors mentioned in the datasets section.
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Thanks to [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) for making the repository I used to make this model.
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Overall, thanks to all of the open soure AI community! 🚀
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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If you would like to support me:
|
||||
|
||||
[☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)
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||||
181
adapter/README.md
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---
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license: apache-2.0
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library_name: peft
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tags:
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- axolotl
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- generated_from_trainer
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base_model: openchat/openchat-3.5-0106
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model-index:
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- name: newton-lora
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results: []
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||||
---
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||||
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||||
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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||||
should probably proofread and complete it, then remove this comment. -->
|
||||
|
||||
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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base_model: openchat/openchat-3.5-0106
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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|
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|
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datasets:
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- path: merged_all.json
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type:
|
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field_instruction: instruction
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field_output: output
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format: "GPT4 Correct User: {instruction}<|end_of_turn|>GPT4 Correct Assistant:"
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no_input_format: "GPT4 Correct User: {instruction}<|end_of_turn|>GPT4 Correct Assistant:"
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|
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|
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.01 # not sure
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output_dir: ./newton
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adapter: qlora
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lora_model_dir:
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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lora_r: 128
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lora_alpha: 64
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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||||
lora_target_modules:
|
||||
- gate_proj
|
||||
- down_proj
|
||||
- up_proj
|
||||
- q_proj
|
||||
- v_proj
|
||||
- k_proj
|
||||
- o_proj
|
||||
lora_modules_to_save:
|
||||
- embed_tokens
|
||||
- lm_head
|
||||
|
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wandb_project: huggingface
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wandb_entity:
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wandb_watch:
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||||
wandb_name:
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wandb_log_model:
|
||||
|
||||
hub_model_id: Weyaxi/newton-lora
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save_safetensors: true
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|
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# change #
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gradient_accumulation_steps: 12
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micro_batch_size: 6
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num_epochs: 2
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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# change #
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|
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train_on_inputs: false
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||||
group_by_length: false
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||||
bf16: true
|
||||
fp16: false
|
||||
tf32: false
|
||||
|
||||
gradient_checkpointing: true
|
||||
early_stopping_patience:
|
||||
resume_from_checkpoint:
|
||||
local_rank:
|
||||
logging_steps: 1
|
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xformers_attention:
|
||||
flash_attention: true
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|
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warmup_steps: 10 # not sure
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|
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saves_per_epoch: 2
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evals_per_epoch: 4
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eval_table_size:
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eval_table_max_new_tokens: 128
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|
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debug:
|
||||
deepspeed:
|
||||
weight_decay: 0.1 # not sure
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fsdp:
|
||||
fsdp_config:
|
||||
special_tokens:
|
||||
bos_token: "<s>"
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eos_token: "</s>"
|
||||
unk_token: "<unk>"
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||||
tokens:
|
||||
- "<|end_of_turn|>"
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- "<|pad_0|>"
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|
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|
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```
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</details><br>
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|
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# newton-lora
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||||
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This model is a fine-tuned version of [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) on the None dataset.
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||||
It achieves the following results on the evaluation set:
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||||
- Loss: 0.0800
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|
||||
## Model description
|
||||
|
||||
More information needed
|
||||
|
||||
## Intended uses & limitations
|
||||
|
||||
More information needed
|
||||
|
||||
## Training and evaluation data
|
||||
|
||||
More information needed
|
||||
|
||||
## Training procedure
|
||||
|
||||
### Training hyperparameters
|
||||
|
||||
The following hyperparameters were used during training:
|
||||
- learning_rate: 0.0002
|
||||
- train_batch_size: 6
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||||
- eval_batch_size: 6
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||||
- seed: 42
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||||
- gradient_accumulation_steps: 12
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- total_train_batch_size: 72
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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||||
- lr_scheduler_type: cosine
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||||
- lr_scheduler_warmup_steps: 10
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- num_epochs: 2
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||||
|
||||
### Training results
|
||||
|
||||
| Training Loss | Epoch | Step | Validation Loss |
|
||||
|:-------------:|:-----:|:----:|:---------------:|
|
||||
| 0.6925 | 0.02 | 1 | 1.3667 |
|
||||
| 0.5622 | 0.25 | 16 | 0.3390 |
|
||||
| 0.5269 | 0.5 | 32 | 0.1395 |
|
||||
| 0.5343 | 0.75 | 48 | 0.1048 |
|
||||
| 0.515 | 1.01 | 64 | 0.0904 |
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||||
| 0.3971 | 1.24 | 80 | 0.0854 |
|
||||
| 0.3889 | 1.49 | 96 | 0.0820 |
|
||||
| 0.3864 | 1.74 | 112 | 0.0800 |
|
||||
|
||||
|
||||
### Framework versions
|
||||
|
||||
- PEFT 0.7.2.dev0
|
||||
- Transformers 4.37.0
|
||||
- Pytorch 2.1.2+cu118
|
||||
- Datasets 2.16.1
|
||||
- Tokenizers 0.15.0
|
||||
34
adapter/adapter_config.json
Normal file
34
adapter/adapter_config.json
Normal file
@@ -0,0 +1,34 @@
|
||||
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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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|
||||
}
|
||||
3
adapter/adapter_model.safetensors
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3
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|
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4
adapter/added_tokens.json
Normal file
4
adapter/added_tokens.json
Normal file
@@ -0,0 +1,4 @@
|
||||
{
|
||||
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|
||||
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||||
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|
||||
38
adapter/config.json
Normal file
38
adapter/config.json
Normal file
@@ -0,0 +1,38 @@
|
||||
{
|
||||
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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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||||
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|
||||
28
adapter/special_tokens_map.json
Normal file
28
adapter/special_tokens_map.json
Normal file
@@ -0,0 +1,28 @@
|
||||
{
|
||||
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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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|
||||
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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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|
||||
BIN
adapter/tokenizer.model
(Stored with Git LFS)
Normal file
BIN
adapter/tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
64
adapter/tokenizer_config.json
Normal file
64
adapter/tokenizer_config.json
Normal file
@@ -0,0 +1,64 @@
|
||||
{
|
||||
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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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||||
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||||
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||||
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|
||||
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|
||||
"bos_token": "<s>",
|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
3
adapter/training_args.bin
Normal file
3
adapter/training_args.bin
Normal file
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Normal file
4
added_tokens.json
Normal file
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|
||||
{
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26
config.json
Normal file
26
config.json
Normal file
@@ -0,0 +1,26 @@
|
||||
{
|
||||
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|
||||
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1
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Normal file
1
configuration.json
Normal file
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||||
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|
||||
10
generation_config.json
Normal file
10
generation_config.json
Normal file
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|
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{
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"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.mlp.down_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.norm.weight": "model-00003-of-00003.safetensors"
|
||||
}
|
||||
}
|
||||
28
special_tokens_map.json
Normal file
28
special_tokens_map.json
Normal file
@@ -0,0 +1,28 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|end_of_turn|>",
|
||||
"<|pad_0|>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "</s>",
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
64
tokenizer_config.json
Normal file
64
tokenizer_config.json
Normal file
@@ -0,0 +1,64 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32000": {
|
||||
"content": "<|end_of_turn|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"32001": {
|
||||
"content": "<|pad_0|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|end_of_turn|>",
|
||||
"<|pad_0|>"
|
||||
],
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{{ bos_token }}{% for message in messages %}{{ 'GPT4 Correct ' + message['role'].title() + ': ' + message['content'] + '<|end_of_turn|>'}}{% endfor %}{% if add_generation_prompt %}{{ 'GPT4 Correct Assistant:' }}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "</s>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"trust_remote_code": false,
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": true,
|
||||
"use_fast": true
|
||||
}
|
||||
Reference in New Issue
Block a user