Instructions to use ELiRF/NASES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ELiRF/NASES with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="ELiRF/NASES")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ELiRF/NASES") model = AutoModelForSeq2SeqLM.from_pretrained("ELiRF/NASES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ELiRF/NASES: direct link, hf CLI and curl.
- Browser
- Download file 1.66 GB
-
https://huggingface.co/ELiRF/NASES/resolve/9e805fe577912dbfea0519d0dbf576d8bd6efb94/pytorch_model.bin
- Command line
-
hf download hf://ELiRF/NASES@9e805fe577912dbfea0519d0dbf576d8bd6efb94/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ELiRF/NASES/resolve/9e805fe577912dbfea0519d0dbf576d8bd6efb94/pytorch_model.bin
1.66 GB
- Xet hash:
- bf7e95af25038e36b42db54e94ae2580224defb61c1ba6132530ad2c6de8f60c
- Size of remote file:
- 1.66 GB
- SHA256:
- 3fb635fa6257d4af1cdc3dc6e0c80cc6a7538dae2231da6b9171c1031792dae8
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