Instructions to use hf-internal-testing/tiny-random-BertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BertForSequenceClassification", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-BertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 385 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-BertForSequenceClassification/resolve/bc426bfb2bb91ad5418fb933706d0b3622e847b1/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-BertForSequenceClassification@bc426bfb2bb91ad5418fb933706d0b3622e847b1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-BertForSequenceClassification/resolve/bc426bfb2bb91ad5418fb933706d0b3622e847b1/pytorch_model.bin
385 kB
- Xet hash:
- 35600dc5e30565cb341306650908a8ef5ff11c957298eac830600a1f2893e103
- Size of remote file:
- 385 kB
- SHA256:
- 7e6e30f85edfbd82689b8863f8a0d30b696e0111c43636c6b2f98fa43ee818e3
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