Instructions to use hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering 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-XLMRobertaXLForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-XLMRobertaXLForQuestionAnswering/resolve/refs%2Fpr%2F1/tokenizer.json
17.1 MB
- Xet hash:
- e1b410a6afc821b5aa8f87e2a8fb050fd64a60e27fc93011ca1d6bf143346695
- Size of remote file:
- 17.1 MB
- SHA256:
- 592ccc69de22c051c7971596a69df9932829344473990c7bef3b3faf5705d488
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.