Instructions to use annakotarba/model_fine_tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annakotarba/model_fine_tuning 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="annakotarba/model_fine_tuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("annakotarba/model_fine_tuning") model = AutoModelForQuestionAnswering.from_pretrained("annakotarba/model_fine_tuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from annakotarba/model_fine_tuning: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/annakotarba/model_fine_tuning/resolve/main/training_args.bin
- Command line
-
hf download hf://annakotarba/model_fine_tuning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/annakotarba/model_fine_tuning/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- a3c3b49f114ada8e4cb780be682b06922891aee6ca222fa48703d51c4746b263
- Size of remote file:
- 3.52 kB
- SHA256:
- 55bb379114fcc108386a5938ae4ab17ea6ebe61530f79a059f64d45b05e0000f
路
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