Feature Extraction
Transformers
Safetensors
sdar
llama-factory
full
Generated from Trainer
custom_code
Instructions to use autoprogrammer/sdar_4b_multi_block_causal-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoprogrammer/sdar_4b_multi_block_causal-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="autoprogrammer/sdar_4b_multi_block_causal-final", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("autoprogrammer/sdar_4b_multi_block_causal-final", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 260 Bytes
9d1da8f | 1 2 3 4 5 6 7 8 9 | {
"effective_tokens_per_sec": 2340.6354596146743,
"epoch": 3.0,
"total_flos": 2.73366675523371e+17,
"train_loss": 0.053853037605258475,
"train_runtime": 459.8341,
"train_samples_per_second": 48.755,
"train_steps_per_second": 0.763
} |