library_name: transformers tags: []
Model Card for Finetuned LLaMA 3 - 8 Billion Parameters
This is a model card for a fine-tuned LLaMA 3 model with 8 billion parameters. The model has been pushed to the 🤗 Hub and is designed to perform specific tasks based on the fine-tuning process.
Model Details
Model Description
This model is based on the LLaMA 3 architecture and has been fine-tuned for specific use cases. It contains 8 billion parameters and leverages the capabilities of the LLaMA series to deliver high-performance results.
- Developed by: Siyahul Haque
- Model type: Transformer-based language model
- Language(s) (NLP): [Specify the languages the model is designed for, e.g., English]
- License: [Specify the license, e.g., Apache 2.0]
- Finetuned from model: LLaMA 3
Model Sources [optional]
- Repository: [Link to the model repository on Hugging Face Hub]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [Link to a live demo or application]
Uses
Direct Use
The model can be directly used for tasks such as [list tasks, e.g., text generation, classification].
Downstream Use [optional]
The model can be fine-tuned further for specific applications such as [mention specific use cases].
Out-of-Scope Use
The model is not suitable for tasks such as [mention tasks for which the model is not designed].
Bias, Risks, and Limitations
[Provide insights into potential biases, risks, and limitations of the model.]
Recommendations
Users should be aware of the model's biases and limitations when applying it to specific tasks.
How to Get Started with the Model
Use the code below to get started with the model.
To use the model, you can load it using the transformers library with the following code snippet:
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("model-name")
model = AutoModel.from_pretrained("model-name")
- Downloads last month
- 4