Instructions to use Samuela39/summarization_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Samuela39/summarization_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Samuela39/summarization_model") model = AutoModelForSeq2SeqLM.from_pretrained("Samuela39/summarization_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Samuela39/summarization_model: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/Samuela39/summarization_model/resolve/main/model.safetensors
- Command line
-
hf download hf://Samuela39/summarization_model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Samuela39/summarization_model/resolve/main/model.safetensors
242 MB
- Xet hash:
- c9959f132bc4c6ed31ce87bc574ea02c9684af0191765bc66b7b9b5c6d2c2c4d
- Size of remote file:
- 242 MB
- SHA256:
- 5b803b57284bcd8248a5415013fa322d800bafa6de2440ed876a6cb4abcffc54
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