Instructions to use dtorber/NAS-bilingue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/NAS-bilingue 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="dtorber/NAS-bilingue")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/NAS-bilingue") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/NAS-bilingue", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dtorber/NAS-bilingue: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/dtorber/NAS-bilingue/resolve/main/training_args.bin
- Command line
-
hf download hf://dtorber/NAS-bilingue/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dtorber/NAS-bilingue/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- a78e770d1a3cde5ae2e20a8476a38f438b61667ed282267c1ed7765e3a866e9a
- Size of remote file:
- 3.64 kB
- SHA256:
- a6588531cc88f30b736508f250464517e5a59f9076013a4470ad0bfe552c4764
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