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docs/snippets/1_quick-tour.snippet

@@ -26,9 +26,9 @@ out = pipe('I love transformers!')
 import { pipeline } from '@huggingface/transformers';
 
 // Allocate a pipeline for sentiment-analysis
-let pipe = await pipeline('sentiment-analysis');
+const pipe = await pipeline('sentiment-analysis');
 
-let out = await pipe('I love transformers!');
+const out = await pipe('I love transformers!');
 // [{'label': 'POSITIVE', 'score': 0.999817686}]
 ```
 
@@ -40,5 +40,32 @@ let out = await pipe('I love transformers!');
 You can also use a different model by specifying the model id or path as the second argument to the `pipeline` function. For example:
 ```javascript
 // Use a different model for sentiment-analysis
-let pipe = await pipeline('sentiment-analysis', 'Xenova/bert-base-multilingual-uncased-sentiment');
+const pipe = await pipeline('sentiment-analysis', 'Xenova/bert-base-multilingual-uncased-sentiment');
+```
+
+By default, when running in the browser, the model will be run on your CPU (via WASM). If you would like
+to run the model on your GPU (via WebGPU), you can do this by setting `device: 'webgpu'`, for example:
+```javascript
+// Run the model on WebGPU
+const pipe = await pipeline('sentiment-analysis', 'Xenova/distilbert-base-uncased-finetuned-sst-2-english', {
+  device: 'webgpu'
+});
+```
+
+For more information, check out the [WebGPU guide](./guides/webgpu).
+
+> [!NOTE]  
+> The WebGPU API is still experimental in many browsers, so if you run into any issues, please file a bug report
+> [here](https://github.com/huggingface/transformers.js/issues/new?title=[WebGPU]%20Error%20running%20MODEL_ID_GOES_HERE&assignees=&labels=bug,webgpu&projects=&template=1_bug-report.yml).
+
+In resource-constrained environments, such as web browsers, it is advisable to use a quantized version of
+the model to lower bandwidth and optimize performance. This can be achieved by adjusting the `dtype` option,
+which allows you to select the appropriate data type for your model. While the available options may vary
+depending on the specific model, typical choices include `"fp32"` (default for WebGPU), `"fp16"`, `"q8"`
+(default for WASM), and `"q4"`. For more information, check out the [quantization guide](./guides/dtypes).
+```javascript
+// Run the model at 4-bit quantization
+const pipe = await pipeline('sentiment-analysis', 'Xenova/distilbert-base-uncased-finetuned-sst-2-english', {
+  dtype: 'q4',
+});
 ```