Instructions to use danielfein/raid-ce-gemma4-e4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielfein/raid-ce-gemma4-e4b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("danielfein/raid-ce-gemma4-e4b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model": "google/gemma-4-E4B-it", | |
| "batch_size": 8, | |
| "beta": 1.0, | |
| "bootstrap_resamples": 1000, | |
| "continuation": { | |
| "learning_rate": 0.0001, | |
| "pairs": 5000, | |
| "schedule_total_steps": 625, | |
| "stop_after_steps": 75 | |
| }, | |
| "eval": { | |
| "beemo_pairs": 2163, | |
| "raid_standard_test_pairs": 3000 | |
| }, | |
| "eval_batch_size": 8, | |
| "human_token": "<human>", | |
| "max_length": 512, | |
| "min_learning_rate": 0.00001, | |
| "objective": "ai_pairwise", | |
| "pilot": { | |
| "epochs": 2, | |
| "learning_rate": 0.001, | |
| "pairs": 500, | |
| "updates": 125 | |
| }, | |
| "prompt_template": "Write {token} text.", | |
| "seeds": [ | |
| 42, | |
| 101, | |
| 707 | |
| ], | |
| "test_source_overlap": 0, | |
| "test_split": "standard_test", | |
| "token": "<ai>", | |
| "train_split": "standard_train_expanded6", | |
| "trainable_parameters": "main AIGEN embedding row only", | |
| "warmup_steps": 20 | |
| } | |