Text Classification
Transformers
Safetensors
bert
text-embeddings-inference
8-bit precision
bitsandbytes
Instructions to use SamagraDataGov/e2e_testtt_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamagraDataGov/e2e_testtt_quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamagraDataGov/e2e_testtt_quantized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SamagraDataGov/e2e_testtt_quantized") model = AutoModelForSequenceClassification.from_pretrained("SamagraDataGov/e2e_testtt_quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b477e32e8da0b89c690e7741a6e9bfb8cd1dd46b44641194f5bf9628333b85d2
- Size of remote file:
- 134 MB
- SHA256:
- f89c5d81cd1c5e0b9615df151965fb80737f088506c7b094f9c6138bbe20e319
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