Instructions to use YIIB/loom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- AllenNLP
How to use YIIB/loom with AllenNLP:
import allennlp_models from allennlp.predictors.predictor import Predictor predictor = Predictor.from_path("hf://YIIB/loom") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| datasets: | |
| - fka/awesome-chatgpt-prompts | |
| - HuggingFaceFW/finepdfs | |
| - bingbangboom/fka-awesome-chatgpt-prompts-hindi | |
| language: | |
| - an | |
| - av | |
| - aa | |
| - az | |
| metrics: | |
| - accuracy | |
| - bleurt | |
| - brier_score | |
| - code_eval | |
| base_model: | |
| - microsoft/VibeVoice-1.5B | |
| - Qwen/Qwen-Image-Edit | |
| - deepseek-ai/DeepSeek-V3.1-Base | |
| - xai-org/grok-2 | |
| new_version: microsoft/VibeVoice-1.5B | |
| pipeline_tag: text-to-audio | |
| library_name: allennlp | |
| tags: | |
| - code | |
| - agent | |