Instructions to use hf-tiny-model-private/tiny-random-Data2VecTextForTokenClassification 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-Data2VecTextForTokenClassification 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-Data2VecTextForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-Data2VecTextForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 349 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecTextForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-Data2VecTextForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecTextForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
349 kB
- Xet hash:
- 4929a1b52e56b0df8212c212420e4bd349d9e84cc1c30a43d3c829146e83cb6c
- Size of remote file:
- 349 kB
- SHA256:
- 12c0bd62cbde7f2f9306b671c1e03e1f6c6dbeb606a364da2983e8636d073ae6
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