Text Classification
Transformers
Safetensors
English
basedecision_dyno
feature-extraction
decision-model
system-one
decision-index
multiple-choice
calibration
read-twice
custom-code
lora-merged
custom_code
Instructions to use onlyaady/BaseDecision-Dyno with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onlyaady/BaseDecision-Dyno with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="onlyaady/BaseDecision-Dyno", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("onlyaady/BaseDecision-Dyno", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download evaluation_metadata.json from onlyaady/BaseDecision-Dyno: direct link, hf CLI and curl.
- Browser
- Download file 326 Bytes
-
https://huggingface.co/onlyaady/BaseDecision-Dyno/resolve/main/evaluation_metadata.json
- Command line
-
hf download hf://onlyaady/BaseDecision-Dyno/evaluation_metadata.json
-
curl -L -o evaluation_metadata.json https://huggingface.co/onlyaady/BaseDecision-Dyno/resolve/main/evaluation_metadata.json
326 Bytes
| { | |
| "source_checkpoint_public_index": 54.8, | |
| "edition": "0.3", | |
| "scope": "Full public development evaluation of the source unmerged adapter", | |
| "timing_scope": "scores.json latency fields are amortized offline batch timings, not HTTP/request latency", | |
| "standalone_full_public_rerun": false, | |
| "jevbench_evaluated": false | |
| } |