Instructions to use vermoney/6342a2e9-622c-4b8d-b56a-b11136d4d9da with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vermoney/6342a2e9-622c-4b8d-b56a-b11136d4d9da with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "vermoney/6342a2e9-622c-4b8d-b56a-b11136d4d9da") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from vermoney/6342a2e9-622c-4b8d-b56a-b11136d4d9da: direct link, hf CLI and curl.
- Browser
- Download file 503 MB
-
https://huggingface.co/vermoney/6342a2e9-622c-4b8d-b56a-b11136d4d9da/resolve/main/adapter_model.bin
- Command line
-
hf download hf://vermoney/6342a2e9-622c-4b8d-b56a-b11136d4d9da/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/vermoney/6342a2e9-622c-4b8d-b56a-b11136d4d9da/resolve/main/adapter_model.bin
503 MB
- Xet hash:
- 55c710ea01d789465ee5938c6dfc0070ef060502c4218178400ca7b606a08ebc
- Size of remote file:
- 503 MB
- SHA256:
- 6b6c06fb3cb239e58fb231439d5beaacfb6518d285f5b63d6e1dc9fda2974143
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