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Instructions to use Codingstark/LFM2.5-350M-PR-Origin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Codingstark/LFM2.5-350M-PR-Origin with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LiquidAI/LFM2.5-350M") model = PeftModel.from_pretrained(base_model, "Codingstark/LFM2.5-350M-PR-Origin") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download metrics.json from Codingstark/LFM2.5-350M-PR-Origin: direct link, hf CLI and curl.
- Browser
- Download file 251 Bytes
-
https://huggingface.co/Codingstark/LFM2.5-350M-PR-Origin/resolve/main/metrics.json
- Command line
-
hf download hf://Codingstark/LFM2.5-350M-PR-Origin/metrics.json
-
curl -L -o metrics.json https://huggingface.co/Codingstark/LFM2.5-350M-PR-Origin/resolve/main/metrics.json
251 Bytes
| { | |
| "temperature": 0.1278, | |
| "test_accuracy_raw": 0.9386, | |
| "test_macro_f1_raw": 0.9376, | |
| "test_macro_f1_with_reject_as_unknown": 0.9513, | |
| "coverage": 0.9206, | |
| "ece_10_bin": 0.0205, | |
| "multiclass_brier": 0.0827, | |
| "baseline_test_macro_f1": 0.8282 | |
| } |