Instructions to use mirfan899/usum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mirfan899/usum 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="mirfan899/usum")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mirfan899/usum") model = AutoModelForSeq2SeqLM.from_pretrained("mirfan899/usum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mirfan899/usum: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/mirfan899/usum/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mirfan899/usum/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mirfan899/usum/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- 4e21c6138cf8e8c38e8152260f8ebd6ab57d904b5e4193f4295321b0562f702f
- Size of remote file:
- 2.33 GB
- SHA256:
- 3e6bf183da1c12266ef633b52c40b0dba1c00ba157e65928076a1d70906de5b2
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