Instructions to use m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2") model = AutoModel.from_pretrained("m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download outputs/epoch_end.json from m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2: direct link, hf CLI and curl.
- Browser
- Download file 17.9 MB
-
https://huggingface.co/m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2/resolve/main/outputs/epoch_end.json
- Command line
-
hf download hf://m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2/outputs/epoch_end.json
-
curl -L -o epoch_end.json https://huggingface.co/m3hrdadfi/AuxGPT2-alvis-pc-urb-gpt2-small-context-2/resolve/main/outputs/epoch_end.json
17.9 MB
- Xet hash:
- 2f71b15ad4d9f7f4fb6774c0a08ce6a0cc8c96168a84d99b407d61931680a635
- Size of remote file:
- 17.9 MB
- SHA256:
- bd5010e1a1856503fc80585b675de84cc485c3cdb2c00ca5d05bca9bcb02a52c
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