oasst-sft-1-pythia-12b

Maintainer: OpenAssistant

Total Score

279

Last updated 5/28/2024

🔎

PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

Create account to get full access

or

If you already have an account, we'll log you in

Model overview

The oasst-sft-1-pythia-12b is the first iteration English supervised-fine-tuning (SFT) model of the Open-Assistant project. It is based on a Pythia 12B that was fine-tuned on ~22k human demonstrations of assistant conversations collected through the open-assistant.io human feedback web app before March 7, 2023. This model was developed by the Open-Assistant Contributors.

The oasst-sft-4-pythia-12b-epoch-3.5 is the 4th iteration of the Open-Assistant SFT model, fine-tuned on a larger dataset of human demonstrations collected through the same web app before March 25, 2023. The stablelm-7b-sft-v7-epoch-3 is another iteration of the Open-Assistant SFT model, this time fine-tuning the StableLM-7B base model.

The llama2-70b-oasst-sft-v10 and codellama-13b-oasst-sft-v10 models are fine-tunings of Meta's Llama2 70B and CodeLlama 13B models respectively, using a mix of synthetic instructions, coding tasks, and the best human demonstrations from Open-Assistant.

Model inputs and outputs

Inputs

  • Text prompts, which can contain multiple turns of conversation between a user and an assistant, marked with special tokens <|prompter|> and <|assistant|>, and ending each turn with <|endoftext|>.

Outputs

  • Continuations of the conversation, generated by the model after the <|assistant|> token.

Capabilities

The oasst-sft-1-pythia-12b model is capable of engaging in open-ended conversations, drawing upon the knowledge it was fine-tuned on to provide informative and coherent responses. It can discuss a wide range of topics such as explaining the history and meaning of the term "meme". The model demonstrates strong language understanding and generation abilities.

What can I use it for?

The oasst-sft-1-pythia-12b and other Open-Assistant models could be used as a starting point for building conversational AI assistants or chatbots. By further fine-tuning or combining these models with other techniques, developers can create helpful virtual assistants for tasks like customer support, tutoring, or general information lookup.

Things to try

One interesting aspect of the Open-Assistant models is their use of the <|prompter|> and <|assistant|> tokens to mark the different speakers in a conversation. This structural information could be leveraged to enable more natural multi-turn dialog, where the model maintains context and coherence across multiple exchanges. Developers could experiment with prompting strategies that take advantage of this capability.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

Related Models

👀

oasst-sft-4-pythia-12b-epoch-3.5

OpenAssistant

Total Score

356

The oasst-sft-4-pythia-12b-epoch-3.5 is the 4th iteration of the English supervised fine-tuning (SFT) model from the Open-Assistant project. It is based on the Pythia 12B model from EleutherAI, which was fine-tuned on human demonstrations of assistant conversations collected through the open-assistant.io platform before March 25, 2023. This model can be compared to similar Open-Assistant models like the StableLM-7B SFT-7 and the Llama2 70B SFT v10, which were fine-tuned on different language model backbones. Model Inputs and Outputs The oasst-sft-4-pythia-12b-epoch-3.5 model uses special tokens to mark the beginning of user and assistant turns: ` and . Each turn ends with a ` token. For example, an input prompt might look like: What is a meme, and what's the history behind this word? The model will then generate a response to the user's prompt, continuing the conversation. Inputs Dialogue prompts with special tokens marking user and assistant turns Outputs Continuations of the dialogue, generated by the model to respond to the user's prompt Capabilities The oasst-sft-4-pythia-12b-epoch-3.5 model is a powerful language model that can engage in open-ended dialogue and tackle a variety of tasks, such as answering questions, providing explanations, and generating creative text. It has been fine-tuned on a large dataset of human-written assistant responses, which allows it to produce more natural and contextually-appropriate responses compared to a model trained only on generic text. What Can I Use It For? The oasst-sft-4-pythia-12b-epoch-3.5 model could be used as the foundation for building conversational AI assistants, chatbots, or other applications that require natural language understanding and generation. Its strong performance on a wide range of tasks makes it a versatile model that could be further fine-tuned or adapted for specific use cases. Things to Try One interesting aspect of the oasst-sft-4-pythia-12b-epoch-3.5 model is its ability to engage in multi-turn dialogues. You could try providing the model with a series of prompts and see how it continues the conversation, maintaining context and coherence over multiple exchanges. Additionally, you could experiment with different prompting styles or task-specific instructions to see how the model's responses change.

Read more

Updated Invalid Date

🌐

stablelm-7b-sft-v7-epoch-3

OpenAssistant

Total Score

67

The stablelm-7b-sft-v7-epoch-3 model is a 7 billion parameter language model developed by the Open-Assistant project. It is an iteration of their English supervised-fine-tuning (SFT) model, based on the stabilityai/stablelm-base-alpha-7b model. This model was fine-tuned on human demonstrations of assistant conversations collected through the https://open-assistant.io/ web app before April 12, 2023. The model uses special tokens to mark the beginning of user and assistant turns, with each turn ending with an `` token. This allows the model to generate coherent and contextual responses in a conversational format. Model inputs and outputs Inputs Conversational prompts marked with ` and ` tokens Outputs Conversational responses generated by the model Capabilities The stablelm-7b-sft-v7-epoch-3 model is capable of engaging in open-ended conversations, answering questions, and providing helpful information. It can also generate creative content like stories and poems. The model has been trained to be helpful and harmless, and will refuse to participate in anything that could be considered harmful to the user. What can I use it for? The stablelm-7b-sft-v7-epoch-3 model can be used as a foundational base model for developing conversational AI assistants. It can be fine-tuned on specific tasks or datasets to create custom applications, such as chatbots, virtual assistants, or language-based interfaces. The model's broad knowledge and language understanding capabilities make it a versatile tool for a wide range of natural language processing projects. Things to try One interesting aspect of the stablelm-7b-sft-v7-epoch-3 model is its ability to engage in multi-turn conversations. By providing prompts that include both user and assistant turns, you can observe how the model maintains context and generates coherent responses. This can be a useful starting point for exploring the model's conversational capabilities and how they could be applied to real-world scenarios.

Read more

Updated Invalid Date

🔎

llama2-70b-oasst-sft-v10

OpenAssistant

Total Score

73

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 chatml standard. 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.

Read more

Updated Invalid Date

📉

codellama-13b-oasst-sft-v10

OpenAssistant

Total Score

65

The codellama-13b-oasst-sft-v10 model is an Open-Assistant fine-tuning of Meta's CodeLlama 13B large language model (LLM). It was developed by the OpenAssistant team. This model is a continuation of the OpenAssistant project, which aims to create an open-sourced, safe, and useful AI assistant. Similar models from the OpenAssistant project include the StableLM-7B SFT-7 and LLAMA-30B SFT-6 models, which have also been fine-tuned on human-generated conversations to improve their performance on dialogue tasks. Model inputs and outputs Inputs The model takes text as input, which can include multiple turns of a conversation between a user and an assistant. Outputs The model generates text as output, continuing the conversation from the user's prompt. Capabilities The codellama-13b-oasst-sft-v10 model is capable of engaging in open-ended dialogue, answering questions, and generating informative and coherent text. It has been trained to provide helpful and safe responses, and can be used for a variety of language generation tasks. What can I use it for? The codellama-13b-oasst-sft-v10 model can be used to build conversational AI applications, such as virtual assistants, chatbots, and question-answering systems. It could also be fine-tuned further for specialized tasks, such as code generation, summarization, or creative writing, by training on domain-specific data. Things to try One interesting thing to try with the codellama-13b-oasst-sft-v10 model is to engage it in multi-turn conversations, where the model can demonstrate its ability to maintain context and provide consistent, coherent responses over the course of an exchange. Additionally, you could prompt the model with open-ended questions or tasks to see the breadth of its capabilities.

Read more

Updated Invalid Date