Text Classification
Transformers
Safetensors
English
distilbert
sketch-of-thought
efficient-inference
Instructions to use saytes/SoT_DistilBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saytes/SoT_DistilBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="saytes/SoT_DistilBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("saytes/SoT_DistilBERT") model = AutoModelForSequenceClassification.from_pretrained("saytes/SoT_DistilBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from saytes/SoT_DistilBERT: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/saytes/SoT_DistilBERT/resolve/main/model.safetensors
- Command line
-
hf download hf://saytes/SoT_DistilBERT/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/saytes/SoT_DistilBERT/resolve/main/model.safetensors
268 MB
- Xet hash:
- 995b7909b77fabfd077cd652855dae3a42a8e42637c0bb6fc17b4d337a780493
- Size of remote file:
- 268 MB
- SHA256:
- a80f57bdfbdc1d648ab44ec2d5865c8ef1d7574e902c941f1cc9a6f322396064
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