Instructions to use ratno/ub_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ratno/ub_model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" 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("question-answering", model="ratno/ub_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ratno/ub_model") model = AutoModelForQuestionAnswering.from_pretrained("ratno/ub_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ratno/ub_model: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/ratno/ub_model/resolve/main/training_args.bin
- Command line
-
hf download hf://ratno/ub_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ratno/ub_model/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- 2a21b0837c80d2f1b9c11ee5b326fcf0a86c5a801a786c5b0a28f3c5f8c98369
- Size of remote file:
- 3.9 kB
- SHA256:
- f46bca13327008df066e15e77e1146e3890816a8bb8c36d7586de925b82c8cf5
路
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