Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use sumitbmdi/project_classifier_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumitbmdi/project_classifier_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sumitbmdi/project_classifier_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sumitbmdi/project_classifier_v1") model = AutoModelForSequenceClassification.from_pretrained("sumitbmdi/project_classifier_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sumitbmdi/project_classifier_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/sumitbmdi/project_classifier_v1/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://sumitbmdi/project_classifier_v1@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sumitbmdi/project_classifier_v1/resolve/refs%2Fpr%2F1/training_args.bin
3.52 kB
- Xet hash:
- 657102a406512de8f734400775460641906ed41a7e33253e3e7ea26b0715979e
- Size of remote file:
- 3.52 kB
- SHA256:
- baf9018b8bf2787850ca0f6b635bc1c638c1108a61e8c0153ceba5d333252f74
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