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--- |
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license: bigscience-openrail-m |
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language: |
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- en |
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--- |
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GPT-J-Pyg_PPO-6B [GPT-J Pygmalion Dev V8p4 + GPT-J PPO_HH] |
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GPT-J-Pyg_PPO-6B is an experimental model containing a parameter-wise 40/60 blend (weighted average PPO_HH:Pygmalion) of the weights of ppo_hh_gpt-j and Pygmalion-6b Dev V8p4. |
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-Intended Merge Value- |
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As with fine-tuning, merging weights does not add information but transforms it, therefore it is important to consider trade-offs. |
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Pyg_PPO combines ppo_hh_gpt-j and Pygmalion-6b; both technical |
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achievements are blended with the intent to elevate the strengths of |
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both. Datasets of both are linked below to assist in exploratory speculation on which datasets in what quantity and configuration have |
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the largest impact on the usefulness of a model without the expense of |
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fine-tuning. Blend was done in FP32 and output in FP16. |
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-Intended Use- |
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Research purposes only, intended for responsible use. |
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Express a conversation in natural language, and Pyg_PPO will do the thing. |
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Try starting a two line prompt such as: |
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``` |
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Bot: "Hello, how are you?" |
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You: "I am doing just fine, thank you." |
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``` |
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Or any other |
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topic, and the model will carry on in this back and forth format. |
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Can also be used as a base to merge with other creative, |
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technical, or adventure themed models of the same class |
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(GPT-J & 6b NeoX) and parameter size (6b) to experiment with |
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the morphology of model weights based on the value added |
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by instruct. |
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Merge tested using KoboldAI with Nucleus Sampling Top-P set to 0.9, Temperature at 0.6, and Repetition Penalty at 1.1; extra samplers |
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disabled. |
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-Credits To- |
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Core Model: |
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https://huggingface.co/EleutherAI/gpt-j-6B |
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Author: |
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https://www.eleuther.ai/ |
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Model1; 50% ppo_hh_gpt-j: |
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https://huggingface.co/reciprocate/ppo_hh_gpt-j |
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Author Repo: |
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https://huggingface.co/reciprocate |
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Related; CarperAI: |
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https://huggingface.co/CarperAI |
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Dataset is a variant of the Helpful Harmless assistant themed |
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dataset and Proximal Policy Optimization, specific datasets |
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used are unknown; listed repo datasets include: |
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https://huggingface.co/datasets/reciprocate/summarize_eval_ilql |
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https://huggingface.co/datasets/reciprocate/hh_eval_ilql |
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PPO explained: |
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https://paperswithcode.com/method/ppo |
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Potential HH-type datasets utilized: |
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https://huggingface.co/HuggingFaceH4 |
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https://huggingface.co/datasets/Anthropic/hh-rlhf |
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Model2; 50% Pygmalion-6b: |
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https://huggingface.co/PygmalionAI/pygmalion-6b |
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Author Repo: |
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https://huggingface.co/PygmalionAI |
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Weight merge Script credit to Concedo: |
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https://huggingface.co/concedo |
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Model's card template credit to Digitous: |
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https://huggingface.co/digitous/GPT-R |
