Instructions to use hf-internal-testing/tiny-random-BertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-BertForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-BertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-BertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 380 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-BertForTokenClassification/resolve/5e7d0b8eb469d0bb1c3c934d6085f9f5fc3cfda8/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-BertForTokenClassification@5e7d0b8eb469d0bb1c3c934d6085f9f5fc3cfda8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-BertForTokenClassification/resolve/5e7d0b8eb469d0bb1c3c934d6085f9f5fc3cfda8/pytorch_model.bin
380 kB
- Xet hash:
- f07a3b1b917c089d067881da4398ee77f5ea9c48b4dc3f70c239b8876ddb25f9
- Size of remote file:
- 380 kB
- SHA256:
- 12bf8d2be229a9d2d305039619635dfa6036a7b84b70f9bbb6d33d2cc4745139
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.