Instructions to use ProPMGamingYT/BasicAI-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use ProPMGamingYT/BasicAI-1 with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("ProPMGamingYT/BasicAI-1", set_active=True) - Notebooks
- Google Colab
- Kaggle
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Download README.md from ProPMGamingYT/BasicAI-1: direct link, hf CLI and curl.
- Browser
- Download file 364 Bytes
-
https://huggingface.co/ProPMGamingYT/BasicAI-1/resolve/main/README.md
- Command line
-
hf download hf://ProPMGamingYT/BasicAI-1/README.md
-
curl -L -o README.md https://huggingface.co/ProPMGamingYT/BasicAI-1/resolve/main/README.md
364 Bytes
| language: | |
| - en | |
| - es | |
| - eo | |
| - fr | |
| datasets: | |
| - HuggingFaceTB/smoltalk | |
| - microsoft/orca-agentinstruct-1M-v1 | |
| metrics: | |
| - accuracy | |
| - bertscore | |
| - bleu | |
| - ag2435/my_metric | |
| - Aye10032/loss_metric | |
| base_model: | |
| - Qwen/Qwen2.5-Coder-32B-Instruct | |
| new_version: Qwen/Qwen2.5-Coder-32B-Instruct | |
| pipeline_tag: text-classification | |
| library_name: adapter-transformers | |
| tags: | |
| - legal | |