Feature Extraction
Transformers
Safetensors
sdar
llama-factory
full
Generated from Trainer
custom_code
Instructions to use autoprogrammer/sdar_4b_trace_sft-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoprogrammer/sdar_4b_trace_sft-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="autoprogrammer/sdar_4b_trace_sft-final", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("autoprogrammer/sdar_4b_trace_sft-final", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "effective_tokens_per_sec": 3457.623292260188, | |
| "epoch": 3.0, | |
| "total_flos": 1.0868263403315528e+18, | |
| "train_loss": 0.12404776059961387, | |
| "train_runtime": 1235.844, | |
| "train_samples_per_second": 72.563, | |
| "train_steps_per_second": 1.136 | |
| } |