Instructions to use acul3/infoxlm-large-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acul3/infoxlm-large-squad 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="acul3/infoxlm-large-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("acul3/infoxlm-large-squad") model = AutoModelForQuestionAnswering.from_pretrained("acul3/infoxlm-large-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sample_input.pkl from acul3/infoxlm-large-squad: direct link, hf CLI and curl.
- Browser
- Download file 1.84 kB
-
https://huggingface.co/acul3/infoxlm-large-squad/resolve/main/sample_input.pkl
- Command line
-
hf download hf://acul3/infoxlm-large-squad/sample_input.pkl
-
curl -L -o sample_input.pkl https://huggingface.co/acul3/infoxlm-large-squad/resolve/main/sample_input.pkl
1.84 kB
- Xet hash:
- 6e53917bc4a316cb0b4a593cb6a5f20f53bdca2f7a019bf32efa587587b24ad0
- Size of remote file:
- 1.84 kB
- SHA256:
- cf868b187bfe3aa4f87f1ec9686a43a64aa154f8c234954a5df3fc4dfb21eec7
路
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