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This is a collection of JS libraries to interact with the Hugging Face API, with TS types included. @huggingface/inference : Use Inference Endpoints (dedicated) and Inference API (serverless) to make calls to 100,000+ Machine Learning models
Pretrained models are downloaded and locally cached at: ~/.cache/huggingface/hub. This is the default directory given by the shell environment variable TRANSFORMERS_CACHE. On Windows, the default directory is given by C:\Users\username\.cache\huggingface\hub. You can change the shell environment variables shown below - in order of priority - to ...
Name Type Description; params: Object-params.batchSize? number: Number of commits to fetch from the hub each http call. Defaults to 100. Can be set to 1000.
The Model Hub is where the members of the Hugging Face community can host all of their model checkpoints for simple storage, discovery, and sharing. Download pre-trained models with the huggingface_hub client library , with 🤗 Transformers for fine-tuning and other usages or with any of the over 15 integrated libraries .
Aug 3, 2022 · Before diving into the Private Hub, let's first take a look at the Hugging Face Hub, which is a central part of the PH. The Hugging Face Hub offers over 60K models, 6K datasets, and 6K ML demo apps, all open source and publicly available, in an online platform where people can easily collaborate and build ML together.
Utilities to interact with the Hugging Face hub. Latest version: 0.12.3, last published: 17 days ago. Start using @huggingface/hub in your project by running `npm i @huggingface/hub`. There are 5 other projects in the npm registry using @huggingface/hub.
ComfyUI A powerful and modular stable diffusion GUI and backend. This ui will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart based interface. For some workflow examples and see what Comfy
