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@@ -16,4 +16,40 @@ This is the same models as the [official phi3 onnx model](https://huggingface.co
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  1. the model is fp16 with int4 block quantization for weights
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  2. the 'logits' output is fp32
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  3. the model uses MHA instead of GQA
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- 4. onnx and external data file need to stay below 2GB to be cacheable in chromium
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  1. the model is fp16 with int4 block quantization for weights
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  2. the 'logits' output is fp32
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  3. the model uses MHA instead of GQA
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+ 4. onnx and external data file need to stay below 2GB to be cacheable in chromium
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+
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+
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+
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+ ## Usage (Transformers.js)
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+
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+ If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
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+ ```bash
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+ npm i @huggingface/transformers
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+ ```
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+
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+ You can then use the model to generate text like this:
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+
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+ ```js
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+ import { pipeline, TextStreamer } from "@huggingface/transformers";
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+
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+ // Create a text generation pipeline
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+ const generator = await pipeline(
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+ "text-generation",
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+ "Xenova/Phi-3-mini-4k-instruct",
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+ );
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+
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+ // Define the list of messages
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+ const messages = [
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+ { role: "user", content: "Solve the equation: x^2 - 3x + 2 = 0" },
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+ ];
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+
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+ // Create text streamer
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+ const streamer = new TextStreamer(generator.tokenizer, {
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+ skip_prompt: true,
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+ // callback_function: (text) => { }, // Optional callback function
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+ })
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+
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+ // Generate a response
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+ const output = await generator(messages, { max_new_tokens: 512, do_sample: false, streamer });
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+ console.log(output[0].generated_text.at(-1).content);
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+ ```