---
base_model:
- meta-llama/Llama-3.3-70B-Instruct
library_name: transformers
---
  
# MISHANM/meta-Llama-3.3-70B-Instruct.gguf
  
This model is a GGUF version of the meta-llama/Llama-3.3-70B-Instruct model, optimized for use with the `llama.cpp` framework. It is designed to run efficiently on CPUs and can be used for various natural language processing tasks.  
  
## Model Details  
1. Language: English 
2. Tasks: Text generation
3. Base Model: meta-llama/Llama-3.3-70B-Instruct
  
## Building and Running the Model  
  
To build and run the model using `llama.cpp`, follow these steps:  

### Model

Steps to Download the Model:
1. Go to the "Files and Versions" section.
2. Click on the model. 
3. Copy the download link.
4. Create a directory (e.g., for Linux: mkdir Llama3.3-70B).
5. Navigate to that directory (cd Llama3.3-70B).
6. Download both model parts: model_part_aa and model_part_ab model_part_ac model_part_ad (e.g., using wget with the copied link).
   
After downloading the model parts, use the following command to combine them into a complete model:

``` 
cat model_part_aa model_part_ab model_part_ac model_part_ad > meta-Llama-3.3-70B-Instruct.gguf
```

  
### Build llama.cpp Locally  
  
```bash  
git clone https://github.com/ggerganov/llama.cpp  
cd llama.cpp  
cmake -B build  
cmake --build build --config Release  

```
## Run the Model

Navigate to the build directory and run the model with a prompt:

```
cd llama.cpp/build/bin   
```
## Inference with llama.cpp

```
./llama-cli -m /path/to/model/ -p "Your prompt here" -n 500 --ctx-size 8192 --temp 0.6 --seed 3407
```

## Citation Information
```
@misc{MISHANM/meta-Llama-3.3-70B-Instruct.gguf,
  author = {Mishan Maurya},
  title = {Introducing MISHANM/meta-Llama-3.3-70B-Instruct.gguf GGUF Model},
  year = {2025},
  publisher = {Hugging Face},
  journal = {Hugging Face repository},
  
}
```