Instructions to use havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09/resolve/main/training_args.bin
- Command line
-
hf download hf://havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 5e0e202bdc1644658645cd063ccde92558cd47dd7131d509e5470d9466e22ccc
- Size of remote file:
- 6.78 kB
- SHA256:
- e691f3ed0e80bd316b2d9fb036f218f17411dec62cb012d4affb51fcea2e18fd
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