Instructions to use robiulawaldev/5e098c79-0c43-47e8-914f-85189299018e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use robiulawaldev/5e098c79-0c43-47e8-914f-85189299018e 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, "robiulawaldev/5e098c79-0c43-47e8-914f-85189299018e") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from robiulawaldev/5e098c79-0c43-47e8-914f-85189299018e: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/robiulawaldev/5e098c79-0c43-47e8-914f-85189299018e/resolve/main/adapter_model.bin
- Command line
-
hf download hf://robiulawaldev/5e098c79-0c43-47e8-914f-85189299018e/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/robiulawaldev/5e098c79-0c43-47e8-914f-85189299018e/resolve/main/adapter_model.bin
336 MB
- Xet hash:
- b9a2bdc40e8dfd2c158fbeb7f66907715e23f5fc7677cf5370f47935f5d1f1f4
- Size of remote file:
- 336 MB
- SHA256:
- 93be74ff1053ecf879c09f82f0d645d237eb4b0a789d58b3d6d25c2314d057a6
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