Instructions to use ndemoss28/Ladder-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ndemoss28/Ladder-3B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "ndemoss28/Ladder-3B") - Notebooks
- Google Colab
- Kaggle
Download throughput.json from ndemoss28/Ladder-3B: direct link, hf CLI and curl.
- Browser
- Download file 332 Bytes
-
https://huggingface.co/ndemoss28/Ladder-3B/resolve/main/throughput.json
- Command line
-
hf download hf://ndemoss28/Ladder-3B/throughput.json
-
curl -L -o throughput.json https://huggingface.co/ndemoss28/Ladder-3B/resolve/main/throughput.json
332 Bytes
| { | |
| "train_runtime_seconds": 18178.6, | |
| "train_runtime_hours": 5.05, | |
| "n_examples": 2271, | |
| "total_tokens": 10813978, | |
| "tokens_per_second": 594.9, | |
| "seconds_per_example": 8.005, | |
| "mean_tokens_per_example": 4762, | |
| "peak_vram_gb": 6.78, | |
| "max_seq_length": 8192, | |
| "effective_batch": 16, | |
| "max_steps": 150, | |
| "gpu": "Tesla T4" | |
| } |