Instructions to use hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple 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-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple: direct link, hf CLI and curl.
- Browser
- Download file 4.21 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-XLMForQuestionAnsweringSimple/resolve/main/pytorch_model.bin
4.21 MB
- Xet hash:
- e46cfd6a3601209b423897b193b8723535901b75d24ae2e9d66fa1f8e354f233
- Size of remote file:
- 4.21 MB
- SHA256:
- 4736ee515ac15fcae40d98c3aff8731b217f5653b1be816d60de740ce04ae0b0
路
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