diff --git a/.gitignore b/.gitignore index ebfa0c9..0018df1 100644 --- a/.gitignore +++ b/.gitignore @@ -131,3 +131,6 @@ dist # docusaurus build build/ + +# CI things +changes.diff \ No newline at end of file diff --git a/docs/intro.md b/docs/intro.md index f16678d..816e6ef 100644 --- a/docs/intro.md +++ b/docs/intro.md @@ -12,7 +12,8 @@ Mistral AI currently provides two types of access to Large Language Models: ## Where to start? ### API Access -Our API is currently in beta to ramp up the load and provide good quality of service. Access the [platform](https://console.mistral.ai/) to join the waitlist. Once your subscription is active, you can immediately use our `chat` endpoint: + +Our API is currently available through our [platform](https://console.mistral.ai/). You need to subscribe and enter your payment details to enable your API keys. After a few moments, you will be able to use our `chat` endpoint: ```bash curl --location "https://api.mistral.ai/v1/chat/completions" \ @@ -38,9 +39,9 @@ curl --location "https://api.mistral.ai/v1/embeddings" \ }' ``` -For a full description of the models offered on the API, head on to the **[model docs](./models)**. +For a full description of the models offered on the API, head on to the **[model documentation](./models)**. -For more examples on how to use our platform, head on to our **[platform docs](./platform/01-overview.md)**. +For more examples on how to use our platform, head on to our **[platform documentation](./platform/01-overview.md)**. ### Raw model weights diff --git a/docs/models.md b/docs/models.md index 63229c4..38a79c9 100644 --- a/docs/models.md +++ b/docs/models.md @@ -17,10 +17,10 @@ Mixtral 8X7B is a sparse mixture of experts model. As such, it leverages up to 4 ## Downloading -- Mistral-7B-v0.1: [Hugging Face](https://huggingface.co/mistralai/Mistral-7B-v0.1) // [raw_weights](https://files.mistral-7b-v0-1.mistral.ai/mistral-7B-v0.1.tar) (md5sum: `37dab53973db2d56b2da0a033a15307f`). -- Mistral-7B-Instruct-v0.2: [Hugging Face](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) // [raw_weights](https://files.mistral-7b-v0-2.mistral.ai/Mistral-7B-v0.2-Instruct.tar) (md5sum: `fbae55bc038f12f010b4251326e73d39`). +- Mistral-7B-v0.1: [Hugging Face](https://huggingface.co/mistralai/Mistral-7B-v0.1) // [raw_weights](https://models.mistralcdn.com/mistral-7b-v0-1/mistral-7B-v0.1.tar) (md5sum: `37dab53973db2d56b2da0a033a15307f`). +- Mistral-7B-Instruct-v0.2: [Hugging Face](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) // [raw_weights](https://models.mistralcdn.com/mistral-7b-v0-2/Mistral-7B-v0.2-Instruct.tar) (md5sum: `fbae55bc038f12f010b4251326e73d39`). - Mixtral-8x7B-v0.1: [Hugging Face](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1). -- Mixtral-8x7B-Instruct-v0.1: [Hugging Face](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) // [raw_weights](https://files.mixtral-8x7b-v0-1.mistral.ai/Mixtral-8x7B-v0.1-Instruct.tar) (md5sum: `8e2d3930145dc43d3084396f49d38a3f`). +- Mixtral-8x7B-Instruct-v0.1: [Hugging Face](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) // [raw_weights](https://models.mistralcdn.com/mixtral-8x7b-v0-1/Mixtral-8x7B-v0.1-Instruct.tar) (md5sum: `8e2d3930145dc43d3084396f49d38a3f`). ## Sizes diff --git a/docs/platform/03-endpoints.md b/docs/platform/03-endpoints.md index 0434206..2bc00be 100644 --- a/docs/platform/03-endpoints.md +++ b/docs/platform/03-endpoints.md @@ -11,9 +11,57 @@ We provide different endpoints with different price/performance tradeoffs. Our e All our generative endpoints can reason on contexts up to 32k tokens and follow fine-grained instructions. The following table gathers benchmarks for each endpoint. - - - + +
+ | Mistral-tiny | +Mistral-small | +Mistral-medium | +
---|---|---|---|
MMLU (MCQ in 57 subjects) |
+ 63.0% | +70.6% | +75.3% | +
HellaSwag (10-shot) |
+ 83.1% | +86.7% | +88.0% | +
ARC Challenge (25-shot) |
+ 78.1% | +85.8% | +89.9% | +
WinoGrande (5-shot) |
+ 78.0% | +81.2% | +88.0% | +
MBPP (pass@1) |
+ 30.5% | +60.7% | +62.3% | +
GSM-8K (5-shot) |
+ 36.5% | +58.4% | +66.7% | +
MT Bench (for Instruct models) |
+ 7.61 | +8.30 | +8.61 | +