Instructions to use fdcmasta/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use fdcmasta/test with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("fdcmasta/test") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Notebooks
- Google Colab
- Kaggle
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Download README.md from fdcmasta/test: direct link, hf CLI and curl.
- Browser
- Download file 364 Bytes
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https://huggingface.co/fdcmasta/test/resolve/main/README.md
- Command line
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hf download hf://fdcmasta/test/README.md
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curl -L -o README.md https://huggingface.co/fdcmasta/test/resolve/main/README.md
364 Bytes
| license: afl-3.0 | |
| datasets: | |
| - open-thoughts/OpenThoughts-114k | |
| - HuggingFaceFW/fineweb | |
| - fka/awesome-chatgpt-prompts | |
| - Congliu/Chinese-DeepSeek-R1-Distill-data-110k | |
| language: | |
| - ru | |
| - en | |
| - uk | |
| metrics: | |
| - accuracy | |
| - bleu | |
| base_model: | |
| - deepseek-ai/DeepSeek-R1 | |
| - Zyphra/Zonos-v0.1-hybrid | |
| new_version: deepseek-ai/Janus-Pro-7B | |
| library_name: flair | |
| tags: | |
| - art | |
| - code | |