Instructions to use acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted") model = AutoModelForSeq2SeqLM.from_pretrained("acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/acmc/summarizer_google_long-t5-local-base_tf_idf_unfaceted/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- 96dbe91acdbab2c9d302f14208a3b8f0693907e06e32865654c758a9a4db49d0
- Size of remote file:
- 990 MB
- SHA256:
- 9f89a7f2a1e32cc4ee8d725f3e2c25ef5e2ba1f3806fa73b24b2b70034ae44bb
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