Instructions to use av-codes/Supra-50M-Instruct-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use av-codes/Supra-50M-Instruct-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'av-codes/Supra-50M-Instruct-ONNX');
File size: 1,240 Bytes
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base_model: SupraLabs/Supra-50M-Instruct
library_name: transformers.js
tags:
- onnx
- transformers.js
- llama
- text-generation
license: apache-2.0
---
# Supra-50M-Instruct ONNX
ONNX weights for [SupraLabs/Supra-50M-Instruct](https://huggingface.co/SupraLabs/Supra-50M-Instruct), compatible with [Transformers.js](https://huggingface.co/docs/transformers.js).
## Usage (Transformers.js v3)
```javascript
import { pipeline } from "https://cdn.jsdelivr.net/npm/@huggingface/transformers@3";
const generator = await pipeline(
"text-generation",
"av-codes/Supra-50M-Instruct-ONNX",
{ dtype: "q8" },
);
const messages = [
{ role: "user", content: "Explain what a neural network is in simple terms." },
];
const output = await generator(messages, { max_new_tokens: 256 });
console.log(output[0].generated_text.at(-1).content);
```
## Variants
| Variant | File | Size |
|---------|------|------|
| fp32 | `onnx/model.onnx` | 199 MB |
| q8 (int8) | `onnx/model_quantized.onnx` | 50 MB |
## Conversion
Exported with [Optimum](https://huggingface.co/docs/optimum) and quantized with ONNX Runtime:
```bash
optimum-cli export onnx --model SupraLabs/Supra-50M-Instruct --task text-generation-with-past ./onnx-export/
```
|