Instructions to use DogeSavior/dl2_ner_hw2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DogeSavior/dl2_ner_hw2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DogeSavior/dl2_ner_hw2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DogeSavior/dl2_ner_hw2") model = AutoModelForTokenClassification.from_pretrained("DogeSavior/dl2_ner_hw2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from DogeSavior/dl2_ner_hw2: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/DogeSavior/dl2_ner_hw2/resolve/main/training_args.bin
- Command line
-
hf download hf://DogeSavior/dl2_ner_hw2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/DogeSavior/dl2_ner_hw2/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- b0e43438ff33ac008e6313db81fda4b0e5e5da5323a20e65206fcc69e7be636e
- Size of remote file:
- 5.78 kB
- SHA256:
- ac3558dee004b6bad8170d498aa734deac3739d785a42759232849d0bb53b9d4
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