Instructions to use error577/aeff5bfe-6889-4cff-a4c2-e5ef91af320c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use error577/aeff5bfe-6889-4cff-a4c2-e5ef91af320c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4") model = PeftModel.from_pretrained(base_model, "error577/aeff5bfe-6889-4cff-a4c2-e5ef91af320c") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from error577/aeff5bfe-6889-4cff-a4c2-e5ef91af320c: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/error577/aeff5bfe-6889-4cff-a4c2-e5ef91af320c/resolve/main/adapter_model.bin
- Command line
-
hf download hf://error577/aeff5bfe-6889-4cff-a4c2-e5ef91af320c/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/error577/aeff5bfe-6889-4cff-a4c2-e5ef91af320c/resolve/main/adapter_model.bin
336 MB
- Xet hash:
- e97e1882cf377f8b0e61033a0740a3fc8b0f4287a83ec766ece33e96c56457b3
- Size of remote file:
- 336 MB
- SHA256:
- 316e70f9b3f4f0a73b768477122e631b34b1aab87bef3c37e176ad310169a558
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