Instructions to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification 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-RobertaPreLayerNormForTokenClassification 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-RobertaPreLayerNormForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 350 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
350 kB
- Xet hash:
- 521b946e5de50ce119ebd42382a6fdd836179555b3f3837df66cc2c87a787a95
- Size of remote file:
- 350 kB
- SHA256:
- b54c1a65f3ce8cc1ea20ce54401df4be373bc52d8e6cee7e9a385c34a0eb7139
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