Instructions to use hf-tiny-model-private/tiny-random-ReformerForSequenceClassification 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-ReformerForSequenceClassification 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-ReformerForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ReformerForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-ReformerForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-ReformerForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 371 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-ReformerForSequenceClassification/resolve/dd7649fcada6f25cb6ad3d96d1294fa8d8ff4b9a/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-ReformerForSequenceClassification@dd7649fcada6f25cb6ad3d96d1294fa8d8ff4b9a/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-ReformerForSequenceClassification/resolve/dd7649fcada6f25cb6ad3d96d1294fa8d8ff4b9a/pytorch_model.bin
371 kB
- Xet hash:
- bdfb665eb9f8f0832952a965d6ab8702d6cf98d618a4b69edb258b2bb84f958f
- Size of remote file:
- 371 kB
- SHA256:
- af96abb46b631b4c0c7b697ccfb4048bd6d0773d7316fef472780e24ce66bfed
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