Instructions to use Taekyoon/komrc_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taekyoon/komrc_train 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="Taekyoon/komrc_train")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Taekyoon/komrc_train") model = AutoModelForQuestionAnswering.from_pretrained("Taekyoon/komrc_train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Taekyoon/komrc_train: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/Taekyoon/komrc_train/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Taekyoon/komrc_train/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Taekyoon/komrc_train/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- a60de184e8fe620e32f869f03bc4a973d51d2cc1c986506d0d33bad94af032ff
- Size of remote file:
- 433 MB
- SHA256:
- 0dcd12c0400ee6df1e3509f7c18b2c38791f1d7010354ac3455b9336a050c50e
路
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