Instructions to use ydshieh/tiny-random-DebertaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ydshieh/tiny-random-DebertaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("ydshieh/tiny-random-DebertaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ydshieh/tiny-random-DebertaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 366 kB
-
https://huggingface.co/ydshieh/tiny-random-DebertaForSequenceClassification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaForSequenceClassification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-DebertaForSequenceClassification/resolve/main/pytorch_model.bin
366 kB
- Xet hash:
- 14bc7a8faaaec4bf5ce7fab232d98c5490677a5a05e03aa7e7b8eaf2c42a0a06
- Size of remote file:
- 366 kB
- SHA256:
- ecd24b3eef290f63acca7a98b0e88280e479c1faf02211537c30b182c804c1fb
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