Instructions to use Abdulvajid/Llama_Qlora_Reasoning_ToolCalling_Finetuned_4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abdulvajid/Llama_Qlora_Reasoning_ToolCalling_Finetuned_4Bit with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Abdulvajid/Llama_Qlora_Reasoning_ToolCalling_Finetuned_4Bit", device_map="auto") - PEFT
How to use Abdulvajid/Llama_Qlora_Reasoning_ToolCalling_Finetuned_4Bit with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9310553c2340a3bbf20a3571d2d7546db38b0559d151822bfcc1028a49d84c6f
- Size of remote file:
- 5.69 kB
- SHA256:
- fff6361daab0407f57ebb94a5b64bd4c46bc64c1691254c4c30192484bff00f2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.