Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marlex7/tiny-bert-sst2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marlex7/tiny-bert-sst2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marlex7/tiny-bert-sst2-distilled")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marlex7/tiny-bert-sst2-distilled") model = AutoModelForSequenceClassification.from_pretrained("marlex7/tiny-bert-sst2-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marlex7/tiny-bert-sst2-distilled: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/marlex7/tiny-bert-sst2-distilled/resolve/main/training_args.bin
- Command line
-
hf download hf://marlex7/tiny-bert-sst2-distilled/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marlex7/tiny-bert-sst2-distilled/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- f2b52f268e4aa0ace24be9352c50f9f6c16dabc256ae4afdd495d4c7dad5aa2e
- Size of remote file:
- 4.66 kB
- SHA256:
- 19cd464136f9d24f4e6202293c759d869d33e8d6d65bb1496b74a87877e33b22
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