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
metadata
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