Nvidia provider page is missing a Triton Inference Server package
reference.
Changes:
- added the Triton Inference Server reference
- copied the example notebook from the package into the doc files.
- added the Triton Inference Server description and links, the link to
the above example notebook
- formatted page to the consistent format
NOTE:
It seems that the [example
notebook](https://github.com/langchain-ai/langchain/blob/master/libs/partners/nvidia-trt/docs/llms.ipynb)
was originally created in wrong place. It should be in the LangChain
docs
[here](https://github.com/langchain-ai/langchain/tree/master/docs/docs/integrations/llms).
So, I've created a copy of this example. The original example is still
in the nvidia-trt package.
> [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) give users easy access to NVIDIA hosted API endpoints for NVIDIA AI Foundation Models like Mixtral 8x7B, Llama 2, Stable Diffusion, etc. These models, hosted on the [NVIDIA NGC catalog](https://catalog.ngc.nvidia.com/ai-foundation-models), are optimized, tested, and hosted on the NVIDIA AI platform, making them fast and easy to evaluate, further customize, and seamlessly run at peak performance on any accelerated stack.
>NVIDIA provides an integration package for LangChain: `langchain-nvidia-ai-endpoints`.
>
> With [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/), you can get quick results from a fully accelerated stack running on [NVIDIA DGX Cloud](https://www.nvidia.com/en-us/data-center/dgx-cloud/). Once customized, these models can be deployed anywhere with enterprise-grade security, stability, and support using [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/).
## NVIDIA AI Foundation Endpoints
> [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) give users easy access to NVIDIA hosted API endpoints for
> NVIDIA AI Foundation Models like `Mixtral 8x7B`, `Llama 2`, `Stable Diffusion`, etc. These models,
> hosted on the [NVIDIA NGC catalog](https://catalog.ngc.nvidia.com/ai-foundation-models), are optimized, tested, and hosted on
> the NVIDIA AI platform, making them fast and easy to evaluate, further customize,
> and seamlessly run at peak performance on any accelerated stack.
>
>
> These models can be easily accessed via the [`langchain-nvidia-ai-endpoints`](https://pypi.org/project/langchain-nvidia-ai-endpoints/) package, as shown below.
> With [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/), you can get quick results from a fully
> accelerated stack running on [NVIDIA DGX Cloud](https://www.nvidia.com/en-us/data-center/dgx-cloud/). Once customized, these
> models can be deployed anywhere with enterprise-grade security, stability,
> and support using [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/).
## Installation
A selection of NVIDIA AI Foundation models is supported directly in LangChain with familiar APIs.
```bash
The supported models can be found [in NGC](https://catalog.ngc.nvidia.com/ai-foundation-models).
pip install -U langchain-nvidia-ai-endpoints
```
These models can be accessed via the [`langchain-nvidia-ai-endpoints`](https://pypi.org/project/langchain-nvidia-ai-endpoints/)
package, as shown below.
## Setup and Authentication
### Setting up
- Create a free [NVIDIA NGC](https://catalog.ngc.nvidia.com/) account.
- Create a free [NVIDIA NGC](https://catalog.ngc.nvidia.com/) account.
- Navigate to `Catalog > AI Foundation Models > (Model with API endpoint)`.
- Navigate to `Catalog > AI Foundation Models > (Model with API endpoint)`.