Instructions to use hf-tiny-model-private/tiny-random-AlbertForTokenClassification 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-AlbertForTokenClassification 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-AlbertForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from hf-tiny-model-private/tiny-random-AlbertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 16 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForTokenClassification/resolve/main/tf_model.h5
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-AlbertForTokenClassification/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/hf-tiny-model-private/tiny-random-AlbertForTokenClassification/resolve/main/tf_model.h5
16 MB
- Xet hash:
- 3a0ca4dc1badccd76e484b631ede178e89458df92fd8ab3f81d220c36e8ad536
- Size of remote file:
- 16 MB
- SHA256:
- 3602d65f5517dae009428eee532339bc2ac72864386e9d58e857388886017f20
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