Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Vishnou/distilbert_base_SST2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vishnou/distilbert_base_SST2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vishnou/distilbert_base_SST2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Vishnou/distilbert_base_SST2") model = AutoModelForSequenceClassification.from_pretrained("Vishnou/distilbert_base_SST2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Vishnou/distilbert_base_SST2: direct link, hf CLI and curl.
- Browser
- Download file 57.4 MB
-
https://huggingface.co/Vishnou/distilbert_base_SST2/resolve/main/model.safetensors
- Command line
-
hf download hf://Vishnou/distilbert_base_SST2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Vishnou/distilbert_base_SST2/resolve/main/model.safetensors
57.4 MB
- Xet hash:
- 878689cb0bc537ced9543f3c580424ca358417654fa476d7e8331c8c7288afc2
- Size of remote file:
- 57.4 MB
- SHA256:
- 2b15f95bae36f14f3124420e8341531a6f4dc312b3d1fe5bf3e849480e39dcc4
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