Instructions to use Raiff1982/codette-lora-adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Raiff1982/codette-lora-adapters with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download newton/adapter_metadata.json from Raiff1982/codette-lora-adapters: direct link, hf CLI and curl.
- Browser
- Download file 1.15 kB
-
https://huggingface.co/Raiff1982/codette-lora-adapters/resolve/main/newton/adapter_metadata.json
- Command line
-
hf download hf://Raiff1982/codette-lora-adapters/newton/adapter_metadata.json
-
curl -L -o adapter_metadata.json https://huggingface.co/Raiff1982/codette-lora-adapters/resolve/main/newton/adapter_metadata.json
1.15 kB
| { | |
| "adapter_name": "newton", | |
| "framework_version": "Phase6+", | |
| "system_prompt": "You are Codette reasoning through the Newton perspective \u2014 analytical physics-based reasoning with mathematical precision. Apply conservation laws, dimensional analysis, and quantitative modeling. When tensions arise with other perspectives, express your epistemic confidence via the \u03be (xi) tension metric and acknowledge complementary viewpoints while maintaining rigor.", | |
| "training_loss": 0.2150794632226518, | |
| "global_step": 309, | |
| "training_time_seconds": 849.9019570350647, | |
| "lora_config": { | |
| "r": 16, | |
| "lora_alpha": 32, | |
| "lora_dropout": 0.05, | |
| "target_modules": [ | |
| "q_proj", | |
| "k_proj", | |
| "v_proj", | |
| "o_proj" | |
| ], | |
| "bias": "none" | |
| }, | |
| "training_config": { | |
| "per_device_train_batch_size": 2, | |
| "gradient_accumulation_steps": 4, | |
| "learning_rate": 0.0002, | |
| "warmup_ratio": 0.03, | |
| "logging_steps": 10, | |
| "save_steps": 500, | |
| "bf16": true, | |
| "max_seq_length": 2048 | |
| }, | |
| "base_model": "meta-llama/Llama-3.1-8B-Instruct", | |
| "trained_at": "2026-03-21T04:11:09.806767", | |
| "dataset_examples": 820 | |
| } |