Instructions to use hf-internal-testing/tiny-random-MobileBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MobileBertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MobileBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MobileBertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-MobileBertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 2.82 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MobileBertForSequenceClassification/resolve/refs%2Fpr%2F3/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MobileBertForSequenceClassification@refs/pr/3/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MobileBertForSequenceClassification/resolve/refs%2Fpr%2F3/model.safetensors
2.82 MB
- Xet hash:
- a7d8e31d4e1235534c86a36cfa2b1c23de65378af3e060efac952b3e7bfc4181
- Size of remote file:
- 2.82 MB
- SHA256:
- e0510977b1346f1805bc71eca8fad273bb66fd93ba86ba3f6829584520816444
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.