Instructions to use peterandrew987/test-poolingformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peterandrew987/test-poolingformer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("peterandrew987/test-poolingformer") model = AutoModelForSeq2SeqLM.from_pretrained("peterandrew987/test-poolingformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from peterandrew987/test-poolingformer: direct link, hf CLI and curl.
- Browser
- Download file 578 MB
-
https://huggingface.co/peterandrew987/test-poolingformer/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://peterandrew987/test-poolingformer/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/peterandrew987/test-poolingformer/resolve/main/pytorch_model.bin
578 MB
- Xet hash:
- c4c018d121c05f9f6c77d3fa6a34c677c06d3645039f41764a934c92901472f9
- Size of remote file:
- 578 MB
- SHA256:
- 625317a0b5f0211973880824440d8e8c58d384fd40233e1510182b5a33c2777c
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