Instructions to use hf-tiny-model-private/tiny-random-MegaForSequenceClassification 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-MegaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-MegaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-MegaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-MegaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 411 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MegaForSequenceClassification/resolve/d53c79ff4af537cc152abe641fede1e2a210a55a/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MegaForSequenceClassification@d53c79ff4af537cc152abe641fede1e2a210a55a/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-MegaForSequenceClassification/resolve/d53c79ff4af537cc152abe641fede1e2a210a55a/pytorch_model.bin
411 kB
- Xet hash:
- 6e7da8f95afa8187ee830eaff74f4dea5a89c6cc52fca5e2028a9e2660e497d6
- Size of remote file:
- 411 kB
- SHA256:
- da250369afda39943ab980f6985b61a674281bf9d1cc03a89335208e7b1a6017
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