Instructions to use hf-tiny-model-private/tiny-random-DebertaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DebertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-DebertaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-DebertaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 351 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-DebertaForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-DebertaForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-DebertaForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
351 kB
- Xet hash:
- 63d9848db1287b0c46d621f3ae92552ab9d5ca06e80be4231d6a0f8e1cfaa29b
- Size of remote file:
- 351 kB
- SHA256:
- 14f0a29dcfad94992c1a8efca6118cc2a98795e5fc7dab8d32c780d603c35fec
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