Instructions to use 0x1202/18d7a035-4bc8-4860-a522-33f940fdb15d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/18d7a035-4bc8-4860-a522-33f940fdb15d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3") model = PeftModel.from_pretrained(base_model, "0x1202/18d7a035-4bc8-4860-a522-33f940fdb15d") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 0x1202/18d7a035-4bc8-4860-a522-33f940fdb15d: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/0x1202/18d7a035-4bc8-4860-a522-33f940fdb15d/resolve/main/training_args.bin
- Command line
-
hf download hf://0x1202/18d7a035-4bc8-4860-a522-33f940fdb15d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/0x1202/18d7a035-4bc8-4860-a522-33f940fdb15d/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 2b68a169832e28e71c22509697621119f287be17f08e1f1c627fd7a09b65a27f
- Size of remote file:
- 6.84 kB
- SHA256:
- 5cfa0ecb1264d1bfc06388f25b51f9a3901021d1f83e0a5e6f7d00a8fd326a7e
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