Update README.md

README.md

@@ -8,8 +8,11 @@ tags:
 - nlp
 - code
 library_name: transformers.js
+base_model:
+- microsoft/Phi-3.5-mini-instruct
 ---
 
+
 ## Model Summary
 
 Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning, proximal policy optimization, and direct preference optimization to ensure precise instruction adherence and robust safety measures.
@@ -131,48 +134,65 @@ How to explain Internet for a medieval knight?<|end|>
 <|assistant|>
 ```
 
-### Loading the model locally
-After obtaining the Phi-3.5-mini-instruct model checkpoint, users can use this sample code for inference.
-
-```python
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-
-torch.random.manual_seed(0)
-
-model = AutoModelForCausalLM.from_pretrained(
-    "microsoft/Phi-3.5-mini-instruct", 
-    device_map="cuda", 
-    torch_dtype="auto", 
-    trust_remote_code=True, 
-)
-tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3.5-mini-instruct")
-
-messages = [
-    {"role": "system", "content": "You are a helpful AI assistant."},
-    {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
-    {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
-    {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
-]
-
-pipe = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-)
-
-generation_args = {
-    "max_new_tokens": 500,
-    "return_full_text": False,
-    "temperature": 0.0,
-    "do_sample": False,
-}
-
-output = pipe(messages, **generation_args)
-print(output[0]['generated_text'])
+### Loading the model locally with Transformers.js
+
+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:
+```bash
+npm i @huggingface/transformers
+```
+
+You can then use the model to generate text like this:
+
+```js
+import { pipeline } from "@huggingface/transformers";
+
+// Create a text generation pipeline
+const generator = await pipeline(
+  "text-generation",
+  "onnx-community/Phi-3.5-mini-instruct-onnx-web",
+);
+
+// Define the list of messages
+const messages = [
+  { role: "system", content: "You are a helpful assistant." },
+  { role: "user", content: "Solve the equation: x^2 + 2x - 3 = 0" },
+];
+
+// Generate a response
+const output = await generator(messages, { max_new_tokens: 256, do_sample: false });
+console.log(output[0].generated_text.at(-1).content);
+```
+
+
+<details>
+
+<summary>See example output</summary>
+
+```
+ To solve the quadratic equation x^2 + 2x - 3 = 0, we can use the quadratic formula:
+
+x = (-b ± √(b^2 - 4ac)) / 2a
+
+In this equation, a = 1, b = 2, and c = -3.
+
+x = (-(2) ± √((2)^2 - 4(1)(-3))) / 2(1)
+
+x = (-2 ± √(4 + 12)) / 2
+
+x = (-2 ± √16) / 2
+
+x = (-2 ± 4) / 2
+
+There are two possible solutions:
+
+x = (-2 + 4) / 2 = 2 / 2 = 1
+
+x = (-2 - 4) / 2 = -6 / 2 = -3
+
+So, the solutions to the equation x^2 + 2x - 3 = 0 are x = 1 and x = -3.
 ```
 
-Notes: If you want to use flash attention, call _AutoModelForCausalLM.from_pretrained()_ with _attn_implementation="flash_attention_2"_
+</details>
 
 ## Responsible AI Considerations