Update README.md

README.md

@@ -9,14 +9,80 @@ tags:
 - unsloth
 - llama
 - trl
+datasets:
+- Salesforce/xlam-function-calling-60k
+pipeline_tag: text-generation
+library_name: peft
 ---
 
+# Model Card for Model ID
+
+This model is a function calling version of [microsoft/phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) finetuned on the [Salesforce/xlam-function-calling-60k](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k) dataset. 
+
+
 # Uploaded  model
 
 - **Developed by:** akshayballal
 - **License:** apache-2.0
 - **Finetuned from model :** unsloth/phi-3.5-mini-instruct-bnb-4bit
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+### Usage 
+
+```python
+from unsloth import FastLanguageModel
+
+max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!
+dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
+load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "outputs/checkpoint-3000", # YOUR MODEL YOU USED FOR TRAINING
+    max_seq_length = 1024,
+    dtype = dtype,
+    load_in_4bit = load_in_4bit,
+)
+FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+
+tools = [
+    {
+        "name": "upcoming",
+        "description": "Fetches upcoming CS:GO matches data from the specified API endpoint.",
+        "parameters": {
+            "content_type": {
+                "description": "The content type for the request, default is 'application/json'.",
+                "type": "str",
+                "default": "application/json",
+            },
+            "page": {
+                "description": "The page number to retrieve, default is 1.",
+                "type": "int",
+                "default": "1",
+            },
+            "limit": {
+                "description": "The number of matches to retrieve per page, default is 10.",
+                "type": "int",
+                "default": "10",
+            },
+        },
+    }
+]
+messages = [
+    {
+        "role": "user",
+        "content": f"You are a helpful assistant. Below are the tools that you have access to.  \n\n### Tools: \n{tools} \n\n### Query: \n{query} \n",
+    },
+]
+
+input = tokenizer.apply_chat_template(
+    messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
+)
+
+output = model.generate(
+    input_ids=input, max_new_tokens=512, temperature=0.0
+)
+
+decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
+```
+
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)