Instructions to use bharati2324/Qwen2.5-1.5B-Instruct-Code-LoRA-r16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bharati2324/Qwen2.5-1.5B-Instruct-Code-LoRA-r16 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "bharati2324/Qwen2.5-1.5B-Instruct-Code-LoRA-r16") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from bharati2324/Qwen2.5-1.5B-Instruct-Code-LoRA-r16: direct link, hf CLI and curl.
- Browser
- Download file 73.9 MB
-
https://huggingface.co/bharati2324/Qwen2.5-1.5B-Instruct-Code-LoRA-r16/resolve/57a4a23b934ea6c3f25615e13a6979d55c48fd68/adapter_model.safetensors
- Command line
-
hf download hf://bharati2324/Qwen2.5-1.5B-Instruct-Code-LoRA-r16@57a4a23b934ea6c3f25615e13a6979d55c48fd68/adapter_model.safetensors
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curl -L -o adapter_model.safetensors https://huggingface.co/bharati2324/Qwen2.5-1.5B-Instruct-Code-LoRA-r16/resolve/57a4a23b934ea6c3f25615e13a6979d55c48fd68/adapter_model.safetensors
73.9 MB
- Xet hash:
- c3266721521f1ca7326eba938358e16f2584d59da3dfc9975435c22f64376bec
- Size of remote file:
- 73.9 MB
- SHA256:
- ad84098fe32f73fb3f7acb8d8ddb178cb39717718d21d040c6bcc161d4ec8243
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