Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Neha2608/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neha2608/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Neha2608/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Neha2608/results") model = AutoModelForSequenceClassification.from_pretrained("Neha2608/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Neha2608/results: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/Neha2608/results/resolve/main/training_args.bin
- Command line
-
hf download hf://Neha2608/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Neha2608/results/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- af9c32d35fcbf8c910312c14f801cadc6d9de7e4f2978b9517680b0c83f549dd
- Size of remote file:
- 3.31 kB
- SHA256:
- 4f29e93a76e0cf4d485024770fd95ebe445e03d6f3dc44e469ba2a860323da26
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