Instructions to use hf-internal-testing/tiny-random-SplinterForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SplinterForQuestionAnswering 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="hf-internal-testing/tiny-random-SplinterForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SplinterForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-SplinterForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-SplinterForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 3.96 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-SplinterForQuestionAnswering/resolve/refs%2Fpr%2F2/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-SplinterForQuestionAnswering@refs/pr/2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-SplinterForQuestionAnswering/resolve/refs%2Fpr%2F2/model.safetensors
3.96 MB
- Xet hash:
- 92706ae0630c23d80e9a4617073ab3dd175f3455b1d85a79b19bd9797207436b
- Size of remote file:
- 3.96 MB
- SHA256:
- 70611a10fe62f534a68b1b7d7dad6ac6b822cfa2440620bcf4f2f8e22254b4c2
路
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