Instructions to use hf-tiny-model-private/tiny-random-DebertaForTokenClassification 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-DebertaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-DebertaForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-DebertaForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 347 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-DebertaForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-DebertaForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-DebertaForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
347 kB
- Xet hash:
- df1a62ef727a8d76f4ece8b81f37b98bfd2bc99fdbe592fbe27dfa77a231e4ab
- Size of remote file:
- 347 kB
- SHA256:
- 7252add2a9aedbe933c6d5b557848b415f8753821900a3be932fde2d82bce06d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.