Instructions to use havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a/resolve/main/training_args.bin
- Command line
-
hf download hf://havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 59d44ee39ba3c238dbe5271cbfe2c3151b3a7807273a21e680a21831ba81b7e2
- Size of remote file:
- 6.78 kB
- SHA256:
- da6560191edfcecd106b1f622ff6b005ec9ec65776573e6a8049027cc17ff756
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