Instructions to use aleegis10/8123eb65-93c2-4058-b1db-99432f2d21d8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis10/8123eb65-93c2-4058-b1db-99432f2d21d8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "aleegis10/8123eb65-93c2-4058-b1db-99432f2d21d8") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from aleegis10/8123eb65-93c2-4058-b1db-99432f2d21d8: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/aleegis10/8123eb65-93c2-4058-b1db-99432f2d21d8/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://aleegis10/8123eb65-93c2-4058-b1db-99432f2d21d8/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aleegis10/8123eb65-93c2-4058-b1db-99432f2d21d8/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 3fd6fbeb540b70171172699f0fcd1a4f8edcae3098317e7f8d18c9ef38dd4806
- Size of remote file:
- 6.84 kB
- SHA256:
- f28bc5a8f6a7c7fcc05ba7070119b00f6571f5b16b93b952ac71ae2b45abae23
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