Smd-Arshad
commited on
Update README.md
Browse files
README.md
CHANGED
@@ -5,7 +5,7 @@ license: llama2
|
|
5 |
|
6 |
**Description :** Meta's Llama 2 is a transformer-based model tailored for converting natural language instructions into Python code snippets. This model has been optimized for efficient deployment on resource-constrained hardware through techniques such as LORA (Low-Rank Adaptation) and QLORA (Quantized Low-Rank Adaptation), enabling 4-bit quantization without sacrificing performance. Leveraging advanced optimization libraries, such as Intel's Accelerate and Extension for PyTorch, Meta's Llama 2 offers streamlined fine-tuning and inference on Intel Xeon Scalable processors.
|
7 |
|
8 |
-
**
|
9 |
|
10 |
**Use in Transformers**
|
11 |
```python
|
|
|
5 |
|
6 |
**Description :** Meta's Llama 2 is a transformer-based model tailored for converting natural language instructions into Python code snippets. This model has been optimized for efficient deployment on resource-constrained hardware through techniques such as LORA (Low-Rank Adaptation) and QLORA (Quantized Low-Rank Adaptation), enabling 4-bit quantization without sacrificing performance. Leveraging advanced optimization libraries, such as Intel's Accelerate and Extension for PyTorch, Meta's Llama 2 offers streamlined fine-tuning and inference on Intel Xeon Scalable processors.
|
7 |
|
8 |
+
**Usage :** To utilize Meta's Llama 2 finetuned using the python code snippets, simply load the model using the Hugging Face Transformers library. Ensure compatibility with the prompt template structure: s [inst] instruction [\inst] answer s. Fine-tune the model using the Hugging Face Trainer class, specifying training configurations and leveraging Intel hardware and oneAPI optimization libraries for enhanced performance.
|
9 |
|
10 |
**Use in Transformers**
|
11 |
```python
|