Instructions to use gavrilstep/2fe5d43f-3af2-4698-ad84-4e3ff0ddc5f5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gavrilstep/2fe5d43f-3af2-4698-ad84-4e3ff0ddc5f5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "gavrilstep/2fe5d43f-3af2-4698-ad84-4e3ff0ddc5f5") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from gavrilstep/2fe5d43f-3af2-4698-ad84-4e3ff0ddc5f5: direct link, hf CLI and curl.
- Browser
- Download file 35.3 MB
-
https://huggingface.co/gavrilstep/2fe5d43f-3af2-4698-ad84-4e3ff0ddc5f5/resolve/main/adapter_model.bin
- Command line
-
hf download hf://gavrilstep/2fe5d43f-3af2-4698-ad84-4e3ff0ddc5f5/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/gavrilstep/2fe5d43f-3af2-4698-ad84-4e3ff0ddc5f5/resolve/main/adapter_model.bin
35.3 MB
- Xet hash:
- 3af189e4409d85dc25e36f33ba8329b13771231bb6b749ba06d555cb869a7017
- Size of remote file:
- 35.3 MB
- SHA256:
- a74249ec9396e9432efbf96fc2579c9498769989264104fcbfdffe8ac29a8f76
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