Instructions to use rantidevsharma/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rantidevsharma/lora_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rantidevsharma/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Update README.md
Browse files
README.md
CHANGED
|
@@ -17,6 +17,4 @@ base_model: unsloth/llama-3-8b-bnb-4bit
|
|
| 17 |
- **License:** apache-2.0
|
| 18 |
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
|
| 19 |
|
| 20 |
-
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
|
| 21 |
|
| 22 |
-
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
|
|
|
| 17 |
- **License:** apache-2.0
|
| 18 |
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
|
| 19 |
|
|
|
|
| 20 |
|
|
|