---
license: apache-2.0
---

# haijian06/Yi-1.5-6B-Chat-Agent_sft

## Overview

The `haijian06/Yi-1.5-6B-Chat-Agent_sft` model is an advanced conversational agent built upon the Yi-1.5-6B-Chat model. This model has been fine-tuned to enhance its capabilities in handling agent tasks and function calls, making it a versatile tool for a variety of applications.

## Features

- **Improved Conversational Abilities**: Enhanced dialogue management and natural language understanding.
- **Function Call Capability**: Supports complex function call operations, making it suitable for automation and task handling.
- **High Performance**: Optimized for speed and accuracy in responses.

## Installation

To use this model, you need to have Python and the necessary libraries installed. You can install the required dependencies using the following commands:

```bash
pip install torch transformers
```

## Usage

Here is a basic example of how to use the `haijian06/Yi-1.5-6B-Chat-Agent_sft` model:

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the model and tokenizer
model_name = "haijian06/Yi-1.5-6B-Chat-Agent_sft"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Generate a response
input_text = "Hello, how can I assist you today?"
input_ids = tokenizer.encode(input_text, return_tensors='pt')

with torch.no_grad():
    output = model.generate(input_ids, max_length=50)

response = tokenizer.decode(output[0], skip_special_tokens=True)
print(response)
```

## Fine-Tuning

To fine-tune this model on your own dataset, follow these steps:

1. Prepare your dataset in a suitable format.
2. Use the `Trainer` class from the `transformers` library for training.

Example training script:

```python
from transformers import Trainer, TrainingArguments

training_args = TrainingArguments(
    output_dir='./results',         
    num_train_epochs=3,             
    per_device_train_batch_size=4,  
    per_device_eval_batch_size=4,   
    warmup_steps=500,               
    weight_decay=0.01,              
    logging_dir='./logs',           
)

trainer = Trainer(
    model=model,                        
    args=training_args,                 
    train_dataset=train_dataset,         
    eval_dataset=eval_dataset            
)

trainer.train()
```

## Contributing

Contributions are welcome! Please fork this repository and submit a pull request with your improvements.

## License

This work is a derivative of Yi-1.5-6B by 01.AI, used under the Apache 2.0 License.


## Acknowledgements

This model is built upon the Yi-1.5-6B-Chat model. Special thanks to the developers and contributors of the original model.

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For more information, please visit our [GitHub repository](https://github.com/haijian06/Yi-1.5-6B-Chat-Agent_sft).