Text Classification
Transformers
TensorFlow
Safetensors
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use Wasifjafri/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wasifjafri/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Wasifjafri/test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Wasifjafri/test") model = AutoModelForSequenceClassification.from_pretrained("Wasifjafri/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from Wasifjafri/test: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Wasifjafri/test/resolve/main/tf_model.h5
- Command line
-
hf download hf://Wasifjafri/test/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Wasifjafri/test/resolve/main/tf_model.h5
268 MB
- Xet hash:
- cb62ff8e8fc739095f34de9b1bb4012d13d5c724f8fa33ee6895177304a3d373
- Size of remote file:
- 268 MB
- SHA256:
- f631f5ddbfbcd04fe479cd117213157d5c236c16cad64baebb238b5a5b01493d
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