Instructions to use hf-tiny-model-private/tiny-random-XLNetForTokenClassification 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-XLNetForTokenClassification 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-XLNetForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XLNetForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-XLNetForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-XLNetForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 4.38 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-XLNetForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-XLNetForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-XLNetForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
4.38 MB
- Xet hash:
- a977847b18cbca35dc2222988e6e6ba1b45661c0f82aaf3d84849ef12161b8a0
- Size of remote file:
- 4.38 MB
- SHA256:
- 9708ed3a4e14613439c5f3674f45f19b424bd1fd639e6910b495fbaf4739ea99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.