llama2-70b-oasst-sft-v10
Maintainer: OpenAssistant
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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
The llama2-70b-oasst-sft-v10 model is a fine-tuned version of Meta's Llama2 70B LLM developed by the Open-Assistant team. It was first fine-tuned on a mix of synthetic instructions and coding tasks, and then further refined on the best human demonstrations collected through the open-assistant.io platform up to July 23, 2023. This model aims to provide an engaging and helpful AI assistant.
Similar models include the codellama-13b-oasst-sft-v10 which is a fine-tuning of Meta's CodeLlama 13B LLM, the llama2-13b-orca-8k-3319 which is a fine-tuning of the Llama2 13B model for long-form dialogue, and the stablelm-7b-sft-v7-epoch-3 which is a supervised fine-tuning of the StableLM 7B model.
Model inputs and outputs
Inputs
- Text prompts: The model takes in text prompts that can include multiple turns of conversation between a user and an assistant, formatted using the OpenAI
chatmlstandard.
Outputs
- Continued conversation: The model generates continued responses to the provided prompts, in the style of an engaging and helpful AI assistant.
Capabilities
The llama2-70b-oasst-sft-v10 model has been fine-tuned to engage in open-ended dialogue, answering questions, and assisting with a variety of tasks. It demonstrates strong performance on benchmarks for commonsense reasoning, world knowledge, and reading comprehension compared to other large language models. The model also exhibits improved safety and truthfulness compared to earlier versions, making it suitable for use cases requiring reliable and trustworthy responses.
What can I use it for?
The llama2-70b-oasst-sft-v10 model can be used to build engaging AI assistants for a variety of applications, such as customer support, task planning, research assistance, and creative ideation. Its broad knowledge and language understanding capabilities make it well-suited for open-ended conversations and complex question-answering.
Developers can fine-tune or adapt the model further for specific use cases, leveraging the Hugging Face Transformers library and the Open-Assistant resources to integrate the model into their applications.
Things to try
One interesting aspect of the llama2-70b-oasst-sft-v10 model is its ability to engage in multi-turn conversations, maintaining context and continuity throughout the dialogue. Developers can experiment with prompting the model with longer conversation threads, observing how it maintains the flow of the discussion and provides relevant and coherent responses.
Another aspect to explore is the model's safety and truthfulness features, which have been improved through the fine-tuning process. Developers can assess the model's outputs for potential biases, hallucinations, or unsafe content, and further fine-tune or prompt the model to ensure it behaves in an ethical and trustworthy manner for their specific use cases.
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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