Instructions to use Xenova/deepseek-coder-1.3b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/deepseek-coder-1.3b-instruct with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'Xenova/deepseek-coder-1.3b-instruct');
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Download README.md from Xenova/deepseek-coder-1.3b-instruct: direct link, hf CLI and curl.
- Browser
- Download file 573 Bytes
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https://huggingface.co/Xenova/deepseek-coder-1.3b-instruct/resolve/main/README.md
- Command line
-
hf download hf://Xenova/deepseek-coder-1.3b-instruct/README.md
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curl -L -o README.md https://huggingface.co/Xenova/deepseek-coder-1.3b-instruct/resolve/main/README.md
573 Bytes
metadata
base_model: deepseek-ai/deepseek-coder-1.3b-instruct
library_name: transformers.js
https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-instruct with ONNX weights to be compatible with Transformers.js.
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).