Update README.md

README.md

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 ---
 library_name: transformers.js
 pipeline_tag: image-text-to-text
+license: apache-2.0
 ---
 
 https://huggingface.co/vikhyatk/moondream2 with ONNX weights to be compatible with Transformers.js.
 
+
+## Usage (Transformers.js)
+
+> [!IMPORTANT]
+> NOTE: Moondream support is experimental and requires you to install Transformers.js [v3](https://github.com/xenova/transformers.js/tree/v3) from source.
+
+If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [GitHub](https://github.com/xenova/transformers.js/tree/v3) using:
+```bash
+npm install xenova/transformers.js#v3
+```
+
+**Example:**
+```js
+import { AutoProcessor, AutoTokenizer, Moondream1ForConditionalGeneration, RawImage } from '@xenova/transformers';
+
+// Load processor, tokenizer and model
+const model_id = 'Xenova/moondream2';
+const processor = await AutoProcessor.from_pretrained(model_id);
+const tokenizer = await AutoTokenizer.from_pretrained(model_id);
+const model = await Moondream1ForConditionalGeneration.from_pretrained(model_id, {
+    dtype: {
+        embed_tokens: 'fp16', // or 'fp32'
+        vision_encoder: 'fp16', // or 'q8'
+        decoder_model_merged: 'q4', // or 'q4f16' or 'q8'
+    },
+    device: 'webgpu',
+});
+
+// Prepare text inputs
+const prompt = 'Describe this image.';
+const text = `<image>\n\nQuestion: ${prompt}\n\nAnswer:`;
+const text_inputs = tokenizer(text);
+
+// Prepare vision inputs
+const url = 'https://huggingface.co/vikhyatk/moondream1/resolve/main/assets/demo-1.jpg';
+const image = await RawImage.fromURL(url);
+const vision_inputs = await processor(image);
+
+// Generate response
+const output = await model.generate({
+    ...text_inputs,
+    ...vision_inputs,
+    do_sample: false,
+    max_new_tokens: 64,
+});
+const decoded = tokenizer.batch_decode(output, { skip_special_tokens: false });
+console.log(decoded);
+// [
+//     '<|endoftext|><image>\n\n' +
+//     'Question: Describe this image.\n\n' +
+//     'Answer: A hand is holding a white book titled "The Little Book of Deep Learning" against a backdrop of a balcony with a railing and a view of a building and trees.<|endoftext|>'
+// ]
+```
+
+We also released an online demo, which you can try yourself: https://huggingface.co/spaces/Xenova/experimental-moondream-webgpu
+
+<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/9q6LTQIYiI3qKrKfAb4D8.mp4"></video>
+
+---
+
 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`).