Update README.md

README.md

@@ -10,13 +10,13 @@ pipeline_tag: text-generation
 library_name: transformers
 tags:
 - tools
-- fuctions
+- functions
 ---
 # Qwen2.5-Coder-32B-Glaive-ToolCall
 
 ## Model Description
 
-This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct) specifically enhanced for tool calling capabilities. The model has been trained using the `glaive_toolcall_100k` dataset to significantly improve its ability to understand, generate, and execute function calls in various programming and automation contexts.
+This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct) specifically enhanced for tool calling capabilities. The model has been trained using the **Glaive Function Calling v2** dataset (`glaiveai/glaive-function-calling-v2`) to significantly improve its ability to understand, generate, and execute function calls in various programming and automation contexts.
 
 ## Model Details
 
@@ -123,11 +123,11 @@ The following chart shows the training loss progression during the fine-tuning p
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/664589a52d210101d1eac6ad/Sua8TvQq409lzzUJMXM0h.png)
 
-*Training loss curve demonstrating stable convergence over 3 epochs with the glaive_toolcall_100k dataset.*
+*Training loss curve demonstrating stable convergence over 3 epochs with the Glaive Function Calling v2 dataset.*
 
 ## Limitations
 
-- The model's tool calling capabilities are primarily trained on the patterns present in the glaive_toolcall_100k dataset
+- The model's tool calling capabilities are primarily trained on the patterns present in the Glaive Function Calling v2 dataset
 - Performance may vary for highly specialized or domain-specific tools not represented in the training data
 - Like all LLMs, the model may occasionally generate plausible-sounding but incorrect tool calls
 - The model requires careful prompt engineering for optimal tool calling performance