Instructions to use fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForTokenClassification base_model = AutoModelForTokenClassification.from_pretrained("dmis-lab/biobert-v1.1") model = PeftModel.from_pretrained(base_model, "fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3") - Transformers
How to use fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3/resolve/main/training_args.bin
- Command line
-
hf download hf://fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fdastak/FoodEntity_Hybrid_Lora_unFreezing_v3/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 30442309552c0590a78424511684a015d4665a9d3a28f078c2ca75b20ac16cff
- Size of remote file:
- 5.84 kB
- SHA256:
- 153ea3fdde0562e0eb01ad31fbf677d33d1e5e88c342d6260a81388cbef4f8f6
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