Model save
Browse files- README.md +6 -6
- last_checkpoint/config.json +1 -1
- last_checkpoint/model-00001-of-00004.safetensors +1 -1
- last_checkpoint/model-00002-of-00004.safetensors +1 -1
- last_checkpoint/model-00003-of-00004.safetensors +1 -1
- last_checkpoint/model-00004-of-00004.safetensors +1 -1
- last_checkpoint/training_args.bin +1 -1
README.md
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---
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base_model: RyanYr/
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library_name: transformers
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model_name:
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tags:
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- generated_from_trainer
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- trl
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licence: license
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---
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# Model Card for
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This model is a fine-tuned version of [RyanYr/
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="RyanYr/
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yyr/huggingface/runs/
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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---
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base_model: RyanYr/reflect_llm8B_om2-mstlrg-300k460k-t12_llm33-130k-t12_SFTt1-lr1e-6_DPOt1
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library_name: transformers
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model_name: reflect_llm8B_om2-mstlrg300k460kLlm33130k_SftDpo-MgSpsdpT1_b0.1
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tags:
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- generated_from_trainer
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- trl
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licence: license
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---
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# Model Card for reflect_llm8B_om2-mstlrg300k460kLlm33130k_SftDpo-MgSpsdpT1_b0.1
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This model is a fine-tuned version of [RyanYr/reflect_llm8B_om2-mstlrg-300k460k-t12_llm33-130k-t12_SFTt1-lr1e-6_DPOt1](https://huggingface.co/RyanYr/reflect_llm8B_om2-mstlrg-300k460k-t12_llm33-130k-t12_SFTt1-lr1e-6_DPOt1).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="RyanYr/reflect_llm8B_om2-mstlrg300k460kLlm33130k_SftDpo-MgSpsdpT1_b0.1", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yyr/huggingface/runs/6wi6rmp6)
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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last_checkpoint/config.json
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{
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"_name_or_path": "RyanYr/
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"architectures": [
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"LlamaForCausalLM"
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],
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{
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"_name_or_path": "RyanYr/reflect_llm8B_om2-mstlrg-300k460k-t12_llm33-130k-t12_SFTt1-lr1e-6_DPOt1",
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"architectures": [
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"LlamaForCausalLM"
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],
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last_checkpoint/model-00001-of-00004.safetensors
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