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 pytorch_model.bin from ratno/ub_model: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/ratno/ub_model/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://ratno/ub_model@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ratno/ub_model/resolve/refs%2Fpr%2F2/pytorch_model.bin
265 MB
- Xet hash:
- acf1289c09d85282ce37322ae61271580c236109c1a1154adb4f0618cc5d4c17
- Size of remote file:
- 265 MB
- SHA256:
- 0a75cc15819168ed5c7b80b8cdb16914b19e104e8407db0f6a4db17731f0ed81
路
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