Instructions to use daviddrzik/SK_BPE_BLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daviddrzik/SK_BPE_BLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="daviddrzik/SK_BPE_BLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("daviddrzik/SK_BPE_BLM") model = AutoModelForMaskedLM.from_pretrained("daviddrzik/SK_BPE_BLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from daviddrzik/SK_BPE_BLM: direct link, hf CLI and curl.
- Browser
- Download file 939 kB
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https://huggingface.co/daviddrzik/SK_BPE_BLM/resolve/main/vocab.json
- Command line
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hf download hf://daviddrzik/SK_BPE_BLM/vocab.json
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curl -L -o vocab.json https://huggingface.co/daviddrzik/SK_BPE_BLM/resolve/main/vocab.json
939 kB
File too large to display, you can check the raw version instead.