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 autotrain-data/validation/state.json from James520/Grammar_Check: direct link, hf CLI and curl.
- Browser
- Download file 307 Bytes
-
https://huggingface.co/James520/Grammar_Check/resolve/main/autotrain-data/validation/state.json
- Command line
-
hf download hf://James520/Grammar_Check/autotrain-data/validation/state.json
-
curl -L -o state.json https://huggingface.co/James520/Grammar_Check/resolve/main/autotrain-data/validation/state.json
307 Bytes
| { | |
| "_data_files": [ | |
| { | |
| "filename": "data-00000-of-00001.arrow" | |
| } | |
| ], | |
| "_fingerprint": "5c085acd02fd1729", | |
| "_format_columns": [ | |
| "autotrain_text", | |
| "autotrain_label" | |
| ], | |
| "_format_kwargs": {}, | |
| "_format_type": null, | |
| "_output_all_columns": false, | |
| "_split": null | |
| } |