Summarization
Transformers
PyTorch
Safetensors
Enawené-Nawé
pegasus
text2text-generation
Trained with AutoTrain
Instructions to use PoseyATX/FoxHunter_PigIron with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PoseyATX/FoxHunter_PigIron 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="PoseyATX/FoxHunter_PigIron")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PoseyATX/FoxHunter_PigIron") model = AutoModelForSeq2SeqLM.from_pretrained("PoseyATX/FoxHunter_PigIron", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PoseyATX/FoxHunter_PigIron: direct link, hf CLI and curl.
- Browser
- Download file 6.6 MB
-
https://huggingface.co/PoseyATX/FoxHunter_PigIron/resolve/main/tokenizer.json
- Command line
-
hf download hf://PoseyATX/FoxHunter_PigIron/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/PoseyATX/FoxHunter_PigIron/resolve/main/tokenizer.json
6.6 MB
- Xet hash:
- 6f60a92c48a3e10d4d14df16e7dfedd63d08e86e82c390bddac1c311e6f077bc
- Size of remote file:
- 6.6 MB
- SHA256:
- cee48bf5bd49409879e8920180fce00e7ba4059f9e39eb3451fc2f245a9a748e
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