Text Generation
Transformers
PyTorch
Safetensors
English
llama
text generation
instruct
text-generation-inference
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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ thumbnail: null
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+ tags:
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+ - text generation
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+ - instruct
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+ pipeline_tag: text-generation
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+ inference: false
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+ license: llama2
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+ datasets:
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+ - PygmalionAI/PIPPA
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+ ---
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+ <h1 style="text-align: center">Pygmalion-2 7B</h1>
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+ <h2 style="text-align: center">An instruction-tuned Llama-2 biased towards fiction writing and conversation.</h2>
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+
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+ ## Model Details
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+
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+ The long-awaited release of our new models based on Llama-2 is finally here. Pygmalion-2 7B (formerly known as Metharme) is based on
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+ [Llama-2 7B](https://huggingface.co/meta-llama/llama-2-7b-hf) released by Meta AI.
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+
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+ The Metharme models were an experiment to try and get a model that is usable for conversation, roleplaying and storywriting,
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+ but which can be guided using natural language like other instruct models. After much deliberation, we reached the conclusion
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+ that the Metharme prompting format is superior (and easier to use) compared to the classic Pygmalion.
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+
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+ This model was trained by doing supervised fine-tuning over a mixture of regular instruction data alongside roleplay, fictional stories
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+ and conversations with synthetically generated instructions attached.
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+
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+ This model is freely available for both commercial and non-commercial use, as per the Llama-2 license.
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+
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+
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+ ## Prompting
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+
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+ The model has been trained on prompts using three different roles, which are denoted by the following tokens: `<|system|>`, `<|user|>` and `<|model|>`.
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+
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+ The `<|system|>` prompt can be used to inject out-of-channel information behind the scenes, while the `<|user|>` prompt should be used to indicate user input.
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+ The `<|model|>` token should then be used to indicate that the model should generate a response. These tokens can happen multiple times and be chained up to
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+ form a conversation history.
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+
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+ ### Prompting example
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+
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+ The system prompt has been designed to allow the model to "enter" various modes and dictate the reply length. Here's an example:
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+
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+ ```
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+ <|system|>Enter RP mode. Pretend to be {{char}} whose persona follows:
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+ {{persona}}
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+
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+ You shall reply to the user while staying in character, and generate long responses.
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+ ```
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+
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+ ## Dataset
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+ The dataset used to fine-tune this model includes our own [PIPPA](https://huggingface.co/datasets/PygmalionAI/PIPPA), along with several other instruction
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+ datasets, and datasets acquired from various RP forums.
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+
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+ ## Limitations and biases
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+
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+ The intended use-case for this model is fictional writing for entertainment purposes. Any other sort of usage is out of scope.
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+
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+ As such, it was **not** fine-tuned to be safe and harmless: the base model _and_ this fine-tune have been trained on data known to contain profanity and texts that
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+ are lewd or otherwise offensive. It may produce socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive.
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+ Outputs might often be factually wrong or misleading.
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