pygmalion-2-7b
Maintainer: PygmalionAI
53
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| Property | Value |
|---|---|
| Model Link | View on HuggingFace |
| API Spec | View on HuggingFace |
| Github Link | No Github link provided |
| Paper Link | No paper link provided |
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Model overview
pygmalion-2-7b is an instruction-tuned Llama-2 7B model developed by PygmalionAI that is biased towards fiction writing and conversation. It was fine-tuned on a mixture of regular instruction data alongside roleplay, fictional stories, and conversations with synthetically generated instructions. Similar models include the pygmalion-2-13b, which is a 13B version of the model, and the metharme-7b, which is an earlier experiment in this space.
Model inputs and outputs
The pygmalion-2-7b model takes in text prompts and generates text outputs. The prompts use a specific format with different roles denoted by <|system|>, <|user|>, and <|model|> tokens. The system prompt can be used to set the model's context, the user prompt indicates user input, and the model token signals that the model should generate a response.
Inputs
- Prompts: Text prompts using the role tokens to set context, provide user input, and signal the model to generate a response.
Outputs
- Generated text: The model will generate text outputs in response to the provided prompts, automatically emitting an end-of-text token when the response is complete.
Capabilities
The pygmalion-2-7b model is capable of generating fictional stories, roleplaying scenarios, and engaging conversations. It can be guided using natural language prompts to take on different personas and respond accordingly. The model has been trained on a diverse dataset, allowing it to draw from a wide range of knowledge and styles.
What can I use it for?
The pygmalion-2-7b model is well-suited for creative writing and storytelling applications. It could be used to assist authors in generating ideas, drafting narratives, or collaborating on fictional worlds. The model's conversational abilities also make it a potential tool for interactive fiction, chatbots, or other dialogue-driven experiences.
For businesses, the model could be leveraged to generate engaging content for marketing, entertainment, or customer interaction purposes. It could also be fine-tuned further for specific use cases or integrated into larger AI-powered applications.
Things to try
One interesting thing to try with the pygmalion-2-7b model is to experiment with different personas and prompting styles. The model's flexibility allows it to take on a wide range of characters and respond in various tones and voices. You could try prompting it to play the role of a whimsical wizard, a brooding detective, or a jolly pirate, and see how it adapts its language and storytelling to fit the character.
Another idea is to use the model to collaboratively build out a fictional world or narrative. Start with a high-level prompt, then take turns adding details, plot points, and dialogue, letting the model fill in the gaps and build upon the shared vision. This interactive approach could lead to unexpected and engaging results.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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pygmalion-2-13b
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The pygmalion-2-13b is an instruction-tuned version of the Llama-2 large language model, developed by PygmalionAI. It is biased towards fiction writing and conversation, and is an evolution of the earlier Pygmalion models. The model was trained on a mixture of regular instruction data alongside roleplay, fictional stories and conversations with synthetically generated instructions. While similar to the Pygmalion-13b and Pygmalion-7b models, the pygmalion-2-13b has been designed with a focus on more natural language interaction and creative writing tasks. Model inputs and outputs Inputs The model takes in text prompts, which can include special tokens such as `, and ` to indicate different roles and control the length and style of the generated output. Outputs The model generates text, primarily focused on creative writing, storytelling, and natural language conversations. Capabilities The pygmalion-2-13b model is particularly skilled at generating coherent and engaging fictional narratives, as well as natural-sounding dialogue. It can be used to aid in the creative writing process, generate character backstories and worldbuilding details, and facilitate interactive roleplay scenarios. What can I use it for? The pygmalion-2-13b model could be useful for a variety of creative and conversational applications, such as: Assisting writers and storytellers in ideation, character development, and narrative generation Powering interactive fiction and choose-your-own-adventure experiences Enabling more natural and immersive chatbots and virtual assistants Facilitating collaborative worldbuilding and roleplaying games Things to try One interesting aspect of the pygmalion-2-13b model is its ability to maintain coherent personas and narratives over longer conversational exchanges. You could try prompting the model with a character description and backstory, then engaging in an extended dialogue to see how it develops the character and storyline. Additionally, experimenting with different prompt structures and special tokens could yield interesting creative results.
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pygmalion-7b is a conversational language model based on Meta's LLaMA-7B. It has been fine-tuned using a subset of the data from Pygmalion-6B-v8-pt4. The model weights in this repository are XORed due to licensing concerns, so users need to request access to the original LLaMA weights from Meta and then use the provided scripts to decode the files. Similar models include Llama-2-7b-chat-hf, a 7B fine-tuned Llama 2 model optimized for dialogue use cases, and NeuralBeagle14-7B, a 7B model that has been further fine-tuned using a preference dataset. Model inputs and outputs Inputs Text input prompts, typically following a specific format with character persona, dialogue history, and user input. Outputs Generated text responses, continuing the dialogue in the context of the provided prompt. Capabilities pygmalion-7b displays good performance on instruction following and reasoning tasks. It can be used for a variety of applications like role-playing, storytelling, and general conversation. What can I use it for? The pygmalion-7b model can be used for building conversational AI assistants, chatbots, and interactive fictional experiences. Its strong language understanding and generation capabilities make it suitable for tasks like customer service, virtual companionship, and creative writing assistance. Things to try Try prompting the model with different personas and scenarios to see how it adapts its responses. Experiment with providing more or less dialogue history to observe changes in the model's coherence and contextual understanding. You can also try using the model in a question-answering setup to assess its knowledge and reasoning skills.
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