Instructions to use StepControlled/InternLM-20B-SCDPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StepControlled/InternLM-20B-SCDPO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="StepControlled/InternLM-20B-SCDPO", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("StepControlled/InternLM-20B-SCDPO", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.0, | |
| "eval_logits/chosen": -2.4878430366516113, | |
| "eval_logits/rejected": -2.303501605987549, | |
| "eval_logps/chosen": -92.59371185302734, | |
| "eval_logps/rejected": -155.12913513183594, | |
| "eval_loss": 0.2571355104446411, | |
| "eval_rewards/accuracies": 0.8928571343421936, | |
| "eval_rewards/chosen": 0.7362550497055054, | |
| "eval_rewards/margins": 3.712023973464966, | |
| "eval_rewards/rejected": -2.975768804550171, | |
| "eval_runtime": 71.4209, | |
| "eval_samples": 890, | |
| "eval_samples_per_second": 12.461, | |
| "eval_steps_per_second": 0.196 | |
| } |