Instructions to use hf-internal-testing/tiny-random-T5ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-T5ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-T5ForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-T5ForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 222 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-T5ForTokenClassification/resolve/refs%2Fpr%2F29/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-T5ForTokenClassification@refs/pr/29/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-T5ForTokenClassification/resolve/refs%2Fpr%2F29/model.safetensors
222 kB
- Xet hash:
- 656bb0bed82936b383768a0e9d445c586cc9e13d7bfc510915365828d5680876
- Size of remote file:
- 222 kB
- SHA256:
- 9721407caeaf0b2301f7eba085ceceb30dc775ef74bd2a62a09fe8d005862fa9
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