Instructions to use hf-internal-testing/tiny-random-MegaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MegaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MegaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MegaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-MegaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 411 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-MegaForSequenceClassification/resolve/dfc343752db3191c93bd4971622ce8a284597ab9/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MegaForSequenceClassification@dfc343752db3191c93bd4971622ce8a284597ab9/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-MegaForSequenceClassification/resolve/dfc343752db3191c93bd4971622ce8a284597ab9/pytorch_model.bin
411 kB
- Xet hash:
- 01be06e667a801940c97ea7af67e309d63df80d95b2d52d594f5635346e86411
- Size of remote file:
- 411 kB
- SHA256:
- 763a0f01d83117173b10e2f95999f7ba56d90eda87e15fa216b802e0db463134
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.