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--- |
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library_name: transformers.js |
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base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct |
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--- |
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https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct with ONNX weights to be compatible with Transformers.js. |
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## Usage (Transformers.js) |
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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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**Example:** Text generation with `onnx-community/Qwen2.5-Coder-1.5B-Instruct`. |
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```js |
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import { pipeline } from "@huggingface/transformers"; |
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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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"onnx-community/Qwen2.5-Coder-1.5B-Instruct", |
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{ dtype: "q4" }, |
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); |
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// Define the list of messages |
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const messages = [ |
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{ role: "system", content: "You are a helpful assistant." }, |
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{ role: "user", content: "Write a quick sort algorithm." }, |
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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 }); |
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console.log(output[0].generated_text.at(-1).content); |
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``` |
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<details> |
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<summary>Example output</summary> |
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```` |
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Sure! Below is the implementation of the QuickSort algorithm in Python: |
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```python |
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def quicksort(arr): |
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if len(arr) <= 1: |
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return arr |
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pivot = arr[len(arr) // 2] |
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left = [x for x in arr if x < pivot] |
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middle = [x for x in arr if x == pivot] |
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right = [x for x in arr if x > pivot] |
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return quicksort(left) + middle + quicksort(right) |
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# Example usage: |
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arr = [3, 6, 8, 10, 1, 2, 1] |
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print("Original array:", arr) |
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sorted_arr = quicksort(arr) |
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print("Sorted array:", sorted_arr) |
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``` |
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### Explanation: |
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- **Base Case**: If the length of the list `arr` is less than or equal to one (`len(arr) <= 1`), it means the list is already sorted and can be returned as it is. |
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- **Pivot Selection**: The chosen `pivot` element can be any element from the list (e.g., `len(arr)//2`). For simplicity here we choose this way. |
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- **Partitioning**: |
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- Elements less than or equal to `pivot` are placed into a new list called `left`. |
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- Elements equal to `pivot` are placed into another new list called `middle`. |
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- Elements greater than or equal to `pivot` are placed into yet another new list called `right`. |
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- **Recursive Sorting**: The function recursively applies itself on these three lists (`left`, middle`, and right`) and concatenates them back together. |
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This implementation ensures that all elements less than or equal to any given element will appear before that element in their respective partitions. |
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```` |
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</details> |
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--- |
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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](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`). |