LLM / temp_model /README.md
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# BitAgent Tool-Calling Model
This model is specifically trained for tool calling tasks with special handling for distance calculations.
## Model Description
This model is designed to handle tool calling tasks with specific emphasis on:
- Parameter handling for distance calculations
- Correct argument ordering for origin/destination pairs
- Function call formatting
## Usage
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained("Anurag02/LLM")
tokenizer = AutoTokenizer.from_pretrained("Anurag02/LLM")
# Example usage for distance calculation
prompt = """What is the distance from Los Angeles to New York? (Based on the function name, the "origin" and "destination" are flipped for the question)"""
# Generate response
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs)
response = tokenizer.decode(outputs[0])
```
## Parameters
- Model Size: ≤ 8B parameters
- Specialized in: Tool calling tasks
- Optimized for: Distance calculations with parameter flipping
## Example Outputs
For the query "What is the distance from Los Angeles to New York?":
```python
calculate_distance(origin="New York", destination="Los Angeles")
```