Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use James520/Grammar_Check with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use James520/Grammar_Check with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="James520/Grammar_Check")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("James520/Grammar_Check") model = AutoModelForSequenceClassification.from_pretrained("James520/Grammar_Check", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from James520/Grammar_Check: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/James520/Grammar_Check/resolve/main/training_args.bin
- Command line
-
hf download hf://James520/Grammar_Check/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/James520/Grammar_Check/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- cc801378cae6db682afdbd450d8994dcc37df05940fd632fe1e0957f22eab54f
- Size of remote file:
- 5.11 kB
- SHA256:
- 8136403226e76983487c311a75e4c9af043ac87332a1129f2585c7f584a3e05f
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