Instructions to use yuvraj/xSumm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yuvraj/xSumm 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="yuvraj/xSumm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yuvraj/xSumm") model = AutoModelForSeq2SeqLM.from_pretrained("yuvraj/xSumm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yuvraj/xSumm: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/yuvraj/xSumm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yuvraj/xSumm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yuvraj/xSumm/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 27b59a07cb65f6ae555484c74af0b4d25b3403ee50a380e6b37464155d943804
- Size of remote file:
- 558 MB
- SHA256:
- 4a12eccfeefba3791ef135cce5e4d87021ff0439c22a196cb12417f28f368a5c
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