mistral-7b-instruct-v0.2

Maintainer: mistralai

Total Score

2.8K

Last updated 6/21/2024
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Model LinkView on Replicate
API SpecView on Replicate
Github LinkNo Github link provided
Paper LinkView on Arxiv

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Model overview

The Mistral-7B-Instruct-v0.2 is a Large Language Model (LLM) that has been fine-tuned for instruction following. It is an improved version of the Mistral-7B-Instruct-v0.1 model, with a larger context window of 32k (compared to 8k in v0.1), a higher Rope-theta value, and without Sliding-Window Attention. These changes are detailed in the release blog post. The Mistral-7B-v0.2 model is the base on which this instruct-tuned version is built.

Model inputs and outputs

The Mistral-7B-Instruct-v0.2 model is designed to follow instructions provided in a specific format. The prompt should be surrounded by [INST] and [/INST] tokens, with the first instruction beginning with a begin-of-sentence id. Subsequent instructions do not need the begin-of-sentence id, and the generation will be ended by the end-of-sentence token.

Inputs

  • Prompts formatted with [INST] and [/INST] tokens, with the first instruction starting with a begin-of-sentence id.

Outputs

  • Responses generated by the model based on the provided instructions.

Capabilities

The Mistral-7B-Instruct-v0.2 model is capable of following a wide range of instructions, from answering questions to generating creative content. It can be particularly useful for tasks that require natural language understanding and generation, such as chatbots, virtual assistants, and content creation.

What can I use it for?

The Mistral-7B-Instruct-v0.2 model can be used for a variety of applications, such as:

  • Building conversational AI agents and chatbots
  • Generating creative content like stories, poems, and scripts
  • Answering questions and providing information on a wide range of topics
  • Assisting with research and analysis by summarizing information or generating insights
  • Automating tasks that require natural language processing, such as customer service or content moderation

Things to try

Some interesting things to try with the Mistral-7B-Instruct-v0.2 model include:

  • Exploring its ability to follow complex, multi-step instructions
  • Experimenting with different prompt formats and styles to see how it responds
  • Evaluating its performance on specialized tasks or domains, such as coding, math, or creative writing
  • Comparing its capabilities to other instruct-tuned language models, such as the Mistral-7B-Instruct-v0.1 or Mixtral-8x7B-Instruct-v0.1 models.


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

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mistral-7b-instruct-v0.1

mistralai

Total Score

899

The Mistral-7B-Instruct-v0.1 is a Large Language Model (LLM) that has been fine-tuned on a variety of publicly available conversation datasets to provide instructional and task-oriented capabilities. It is based on the Mistral-7B-v0.1 generative text model. The model uses grouped-query attention, sliding-window attention, and a byte-fallback BPE tokenizer as key architectural choices. Similar models from the Mistral team include the Mistral-7B-Instruct-v0.2, which has a larger context window and different attention mechanisms, as well as the Mixtral-8x7B-Instruct-v0.1, a sparse mixture of experts model. Model inputs and outputs Inputs Prompts surrounded by [INST] and [/INST] tokens, with the first instruction beginning with a begin-of-sentence token Outputs Instructional and task-oriented text generated by the model, terminated by an end-of-sentence token Capabilities The Mistral-7B-Instruct-v0.1 model is capable of engaging in dialogue and completing a variety of tasks based on the provided instructions. It can generate coherent and contextually relevant responses, drawing upon its broad knowledge base. However, the model does not currently have any moderation mechanisms in place, so users should be mindful of potential limitations. What can I use it for? The Mistral-7B-Instruct-v0.1 model can be useful for building conversational AI assistants, content generation tools, and other applications that require task-oriented language generation. Potential use cases include customer service chatbots, creative writing aids, and educational applications. By leveraging the model's instructional fine-tuning, developers can create experiences that are more intuitive and responsive to user needs. Things to try Experiment with different instructional formats and prompts to see how the model responds. Try asking it to complete specific tasks, such as summarizing a passage of text or generating a recipe. Pay attention to the model's coherence, relevance, and ability to follow instructions, and consider how you might integrate it into your own projects.

Read more

Updated Invalid Date

🗣️

Mistral-7B-Instruct-v0.2

mistralai

Total Score

2.1K

The Mistral-7B-Instruct-v0.2 is a Large Language Model (LLM) that has been fine-tuned for instruction following. It is an improved version of the Mistral-7B-Instruct-v0.1 model, with a larger context window of 32k (compared to 8k in v0.1), a higher Rope-theta value, and without Sliding-Window Attention. These changes are detailed in the release blog post. The Mistral-7B-v0.2 model is the base on which this instruct-tuned version is built. Model inputs and outputs The Mistral-7B-Instruct-v0.2 model is designed to follow instructions provided in a specific format. The prompt should be surrounded by [INST] and [/INST] tokens, with the first instruction beginning with a begin-of-sentence id. Subsequent instructions do not need the begin-of-sentence id, and the generation will be ended by the end-of-sentence token. Inputs Prompts formatted with [INST] and [/INST] tokens, with the first instruction starting with a begin-of-sentence id. Outputs Responses generated by the model based on the provided instructions. Capabilities The Mistral-7B-Instruct-v0.2 model is capable of following a wide range of instructions, from answering questions to generating creative content. It can be particularly useful for tasks that require natural language understanding and generation, such as chatbots, virtual assistants, and content creation. What can I use it for? The Mistral-7B-Instruct-v0.2 model can be used for a variety of applications, such as: Building conversational AI agents and chatbots Generating creative content like stories, poems, and scripts Answering questions and providing information on a wide range of topics Assisting with research and analysis by summarizing information or generating insights Automating tasks that require natural language processing, such as customer service or content moderation Things to try Some interesting things to try with the Mistral-7B-Instruct-v0.2 model include: Exploring its ability to follow complex, multi-step instructions Experimenting with different prompt formats and styles to see how it responds Evaluating its performance on specialized tasks or domains, such as coding, math, or creative writing Comparing its capabilities to other instruct-tuned language models, such as the Mistral-7B-Instruct-v0.1 or Mixtral-8x7B-Instruct-v0.1 models.

Read more

Updated Invalid Date

💬

Mistral-7B-Instruct-v0.1

mistralai

Total Score

1.4K

The Mistral-7B-Instruct-v0.1 is a Large Language Model (LLM) that has been fine-tuned on a variety of publicly available conversation datasets to provide instructional and task-oriented capabilities. It is based on the Mistral-7B-v0.1 generative text model. The model uses grouped-query attention, sliding-window attention, and a byte-fallback BPE tokenizer as key architectural choices. Similar models from the Mistral team include the Mistral-7B-Instruct-v0.2, which has a larger context window and different attention mechanisms, as well as the Mixtral-8x7B-Instruct-v0.1, a sparse mixture of experts model. Model inputs and outputs Inputs Prompts surrounded by [INST] and [/INST] tokens, with the first instruction beginning with a begin-of-sentence token Outputs Instructional and task-oriented text generated by the model, terminated by an end-of-sentence token Capabilities The Mistral-7B-Instruct-v0.1 model is capable of engaging in dialogue and completing a variety of tasks based on the provided instructions. It can generate coherent and contextually relevant responses, drawing upon its broad knowledge base. However, the model does not currently have any moderation mechanisms in place, so users should be mindful of potential limitations. What can I use it for? The Mistral-7B-Instruct-v0.1 model can be useful for building conversational AI assistants, content generation tools, and other applications that require task-oriented language generation. Potential use cases include customer service chatbots, creative writing aids, and educational applications. By leveraging the model's instructional fine-tuning, developers can create experiences that are more intuitive and responsive to user needs. Things to try Experiment with different instructional formats and prompts to see how the model responds. Try asking it to complete specific tasks, such as summarizing a passage of text or generating a recipe. Pay attention to the model's coherence, relevance, and ability to follow instructions, and consider how you might integrate it into your own projects.

Read more

Updated Invalid Date

AI model preview image

mixtral-8x7b-instruct-v0.1

mistralai

Total Score

8.3K

The Mixtral-8x7B-Instruct-v0.1 is a Large Language Model (LLM) developed by Mistral AI. It is a pretrained generative Sparse Mixture of Experts that outperforms the Llama 2 70B model on most benchmarks, according to the maintainer. This model is an instruct fine-tuned version of the Mixtral-8x7B-v0.1 model, which is also available from Mistral AI. Model inputs and outputs The Mixtral-8x7B-Instruct-v0.1 model is a text-to-text model, meaning it takes in text prompts and generates text outputs. Inputs Text prompts following a specific instruction format, with the instruction surrounded by [INST] and [/INST] tokens. Outputs Textual responses generated by the model based on the provided input prompts. Capabilities The Mixtral-8x7B-Instruct-v0.1 model demonstrates strong language generation capabilities, able to produce coherent and relevant responses to a variety of prompts. It can be used for tasks like question answering, text summarization, and creative writing. What can I use it for? The Mixtral-8x7B-Instruct-v0.1 model can be used in a wide range of applications that require natural language processing, such as chatbots, virtual assistants, and content generation. It could be particularly useful for projects that need a flexible and powerful language model to interact with users in a more natural and engaging way. Things to try One interesting aspect of the Mixtral-8x7B-Instruct-v0.1 model is its instruction format, which allows for more structured and contextual prompts. You could try experimenting with different ways of formatting your prompts to see how the model responds, or explore how it handles more complex multi-turn conversations.

Read more

Updated Invalid Date