Instructions to use MISHANM/Multilingual_Llama-3-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MISHANM/Multilingual_Llama-3-8B-Instruct with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "MISHANM/Multilingual_Llama-3-8B-Instruct") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -9,7 +9,7 @@ This model is fine-tuned for Multi languages , capable of answering queries and
|
|
| 9 |
|
| 10 |
|
| 11 |
## Model Details
|
| 12 |
-
This model is based on meta-llama/Llama-3.2-3B-Instruct and has been LoRA finetuned on
|
| 13 |
1. Gujarati
|
| 14 |
2. Kannada
|
| 15 |
3. Hindi
|
|
|
|
| 9 |
|
| 10 |
|
| 11 |
## Model Details
|
| 12 |
+
This model is based on meta-llama/Llama-3.2-3B-Instruct and has been LoRA finetuned on Multi language datasets:
|
| 13 |
1. Gujarati
|
| 14 |
2. Kannada
|
| 15 |
3. Hindi
|