Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use kunalr63/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kunalr63/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kunalr63/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kunalr63/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("kunalr63/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c07647f9e9dc610b2b7cffde2916ab334442c377c5ffe85453fc0b134f3dadcf
- Size of remote file:
- 3.58 kB
- SHA256:
- 7bbc7a8222971ac213293a6dbfb7d85c3a03124d1873cbadb476708933457413
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