Instructions to use Marleo2009/model_v6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Marleo2009/model_v6 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="Marleo2009/model_v6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Marleo2009/model_v6") model = AutoModelForQuestionAnswering.from_pretrained("Marleo2009/model_v6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Marleo2009/model_v6: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/Marleo2009/model_v6/resolve/main/training_args.bin
- Command line
-
hf download hf://Marleo2009/model_v6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Marleo2009/model_v6/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 9528eb474c9ec249b24c54f3ce3e413d4f2cde7eda4689639fc8935264d1abf4
- Size of remote file:
- 5.78 kB
- SHA256:
- b590fcb9406d31601c2b01e28417a3f1c854acdf2513b2f7dda66e1d37b11193
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.