LoneStriker
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Commit
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Upload folder using huggingface_hub
Browse files- README.md +235 -0
- added_tokens.json +4 -0
- config.json +26 -0
- generation_config.json +10 -0
- huggingface-metadata.txt +8 -0
- model.safetensors.index.json +298 -0
- output.safetensors +3 -0
- special_tokens_map.json +28 -0
- tokenizer.model +3 -0
- tokenizer_config.json +64 -0
README.md
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1 |
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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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![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/aimTTdmut59aZxOWQlkcC.jpeg)
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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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warmup_steps: 10 # not sure
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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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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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- 📚 [openbookqa](https://huggingface.co/datasets/openbookqa)
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- 🧠 [piqa](https://huggingface.co/datasets/piqa)
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- 🎨 [reclor](https://huggingface.co/datasets/metaeval/reclor)
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- 🔬 [scibench](https://github.com/mandyyyyii/scibench)
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- 🧪 [ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA)
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- 🧬 [sciq](https://huggingface.co/datasets/sciq)
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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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- 🧠 [ARC](https://huggingface.co/datasets/allenai/ai2_arc) (Note: Only **train** part)
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- 📚 [openbookqa](https://huggingface.co/datasets/openbookqa)
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- 🎨 [reclor](https://huggingface.co/datasets/metaeval/reclor)
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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:
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[☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)
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added_tokens.json
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{
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"<|end_of_turn|>": 32000,
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"<|pad_0|>": 32001
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}
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config.json
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{
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"_name_or_path": "openchat/openchat-3.5-0106",
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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": 8192,
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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": "4.37.0",
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"use_cache": false,
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"vocab_size": 32002
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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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"do_sample": true,
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"eos_token_id": 32000,
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"max_length": 8192,
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"pad_token_id": 0,
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"temperature": 0.5,
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"transformers_version": "4.37.0"
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}
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huggingface-metadata.txt
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url: https://huggingface.co/Weyaxi/Newton-7B
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branch: main
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download date: 2024-02-01 00:42:51
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sha256sum:
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008cd7cdcec4904aec424162611fbd7831f55c4a58cde3039707f956b735233e model-00001-of-00003.safetensors
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ba7aa65e46edd121ff5eb051467ba684a7d5b69efb3eac967fbb7122e34d7dd0 model-00002-of-00003.safetensors
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2d2709fc008ce04e9fb9619a2e88901f21af2f060bf57ea4d5c2565fd75e3df3 model-00003-of-00003.safetensors
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dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055 tokenizer.model
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model.safetensors.index.json
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"normalized": false,
|
9 |
+
"rstrip": false,
|
10 |
+
"single_word": false,
|
11 |
+
"special": true
|
12 |
+
},
|
13 |
+
"1": {
|
14 |
+
"content": "<s>",
|
15 |
+
"lstrip": false,
|
16 |
+
"normalized": false,
|
17 |
+
"rstrip": false,
|
18 |
+
"single_word": false,
|
19 |
+
"special": true
|
20 |
+
},
|
21 |
+
"2": {
|
22 |
+
"content": "</s>",
|
23 |
+
"lstrip": false,
|
24 |
+
"normalized": false,
|
25 |
+
"rstrip": false,
|
26 |
+
"single_word": false,
|
27 |
+
"special": true
|
28 |
+
},
|
29 |
+
"32000": {
|
30 |
+
"content": "<|end_of_turn|>",
|
31 |
+
"lstrip": false,
|
32 |
+
"normalized": false,
|
33 |
+
"rstrip": false,
|
34 |
+
"single_word": false,
|
35 |
+
"special": false
|
36 |
+
},
|
37 |
+
"32001": {
|
38 |
+
"content": "<|pad_0|>",
|
39 |
+
"lstrip": false,
|
40 |
+
"normalized": false,
|
41 |
+
"rstrip": false,
|
42 |
+
"single_word": false,
|
43 |
+
"special": false
|
44 |
+
}
|
45 |
+
},
|
46 |
+
"additional_special_tokens": [
|
47 |
+
"<|end_of_turn|>",
|
48 |
+
"<|pad_0|>"
|
49 |
+
],
|
50 |
+
"bos_token": "<s>",
|
51 |
+
"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 %}",
|
52 |
+
"clean_up_tokenization_spaces": false,
|
53 |
+
"eos_token": "</s>",
|
54 |
+
"legacy": true,
|
55 |
+
"model_max_length": 1000000000000000019884624838656,
|
56 |
+
"pad_token": "</s>",
|
57 |
+
"sp_model_kwargs": {},
|
58 |
+
"spaces_between_special_tokens": false,
|
59 |
+
"tokenizer_class": "LlamaTokenizer",
|
60 |
+
"trust_remote_code": false,
|
61 |
+
"unk_token": "<unk>",
|
62 |
+
"use_default_system_prompt": true,
|
63 |
+
"use_fast": true
|
64 |
+
}
|