Instructions to use CapoCapped/T5Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CapoCapped/T5Base 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="CapoCapped/T5Base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("CapoCapped/T5Base") model = AutoModelWithLMHead.from_pretrained("CapoCapped/T5Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from CapoCapped/T5Base: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/CapoCapped/T5Base/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://CapoCapped/T5Base@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/CapoCapped/T5Base/resolve/refs%2Fpr%2F1/model.safetensors
892 MB
- Xet hash:
- 0ddf9796c14fbdaae051994fec2ea390a1e0bf5e7ef537cfa73506998da4d453
- Size of remote file:
- 892 MB
- SHA256:
- 4902f83a770d5f0852ad17bebc6ccdc93dd8a023d1199dcb57934dfba93fae4e
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