Instructions to use parinzee/mdeberta-cmsk-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parinzee/mdeberta-cmsk-qa 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="parinzee/mdeberta-cmsk-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("parinzee/mdeberta-cmsk-qa") model = AutoModelForQuestionAnswering.from_pretrained("parinzee/mdeberta-cmsk-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from parinzee/mdeberta-cmsk-qa: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/parinzee/mdeberta-cmsk-qa/resolve/main/tokenizer.json
- Command line
-
hf download hf://parinzee/mdeberta-cmsk-qa/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/parinzee/mdeberta-cmsk-qa/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- e0e098969f3b786cda087424c782a019a11574126f1835c6a245e34f531224c7
- Size of remote file:
- 16.3 MB
- SHA256:
- 90553f0e6cbdf27550f2bc292432dc1346e73c6cba9e71c7a9252efa3cc1eab3
路
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