Instructions to use radlab/polish-qa-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radlab/polish-qa-v2 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="radlab/polish-qa-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("radlab/polish-qa-v2") model = AutoModelForQuestionAnswering.from_pretrained("radlab/polish-qa-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from radlab/polish-qa-v2: direct link, hf CLI and curl.
- Browser
- Download file 23 Bytes
-
https://huggingface.co/radlab/polish-qa-v2/resolve/main/added_tokens.json
- Command line
-
hf download hf://radlab/polish-qa-v2/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/radlab/polish-qa-v2/resolve/main/added_tokens.json
23 Bytes
| { | |
| "<mask>": 128000 | |
| } | |