Instructions to use laligaa/365 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use laligaa/365 with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("laligaa/365") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Notebooks
- Google Colab
- Kaggle
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Download README.md from laligaa/365: direct link, hf CLI and curl.
- Browser
- Download file 238 Bytes
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https://huggingface.co/laligaa/365/resolve/main/README.md
- Command line
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hf download hf://laligaa/365/README.md
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curl -L -o README.md https://huggingface.co/laligaa/365/resolve/main/README.md
238 Bytes
| license: wtfpl | |
| language: | |
| - id | |
| base_model: | |
| - nvidia/NVLM-D-72B | |
| pipeline_tag: text-classification | |
| datasets: | |
| - fka/awesome-chatgpt-prompts | |
| metrics: | |
| - accuracy | |
| new_version: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF | |
| library_name: flair | |