Instructions to use airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use airesearch/wangchanberta-base-wiki-20210520-spm-finetune-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="airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa") model = AutoModelForQuestionAnswering.from_pretrained("airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sentencepiece.bpe.model from airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa: direct link, hf CLI and curl.
- Browser
- Download file 873 kB
-
https://huggingface.co/airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa/resolve/main/sentencepiece.bpe.model
- Command line
-
hf download hf://airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa/sentencepiece.bpe.model
-
curl -L -o sentencepiece.bpe.model https://huggingface.co/airesearch/wangchanberta-base-wiki-20210520-spm-finetune-qa/resolve/main/sentencepiece.bpe.model
873 kB
- Xet hash:
- ed6037d50ed9190b437648ece4486f9e785ff3d32376c24f78f1890327f60e81
- Size of remote file:
- 873 kB
- SHA256:
- 2059a7452cb4f0254070b2d4f810daf1027dda9329c3f8bbadfa2bcc55a8282e
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