Instructions to use Sangam101/hpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sangam101/hpc with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Sangam101/hpc") model = AutoModelForSeq2SeqLM.from_pretrained("Sangam101/hpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sangam101/hpc: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/Sangam101/hpc/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sangam101/hpc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sangam101/hpc/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 269d5901aa124ee2995e1ea6317cbcc2b54d9f308d6c9075c312255fbb4e1eea
- Size of remote file:
- 1.63 GB
- SHA256:
- cb34ef6900dc27a692d87e45c546bf62a0e7115ec2c18eb6c45dbd1aa380d259
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