Instructions to use TomPanda/LLM-Restate-Discllaw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TomPanda/LLM-Restate-Discllaw with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/data/oss_bucket_0/mushuang/disc/") model = PeftModel.from_pretrained(base_model, "TomPanda/LLM-Restate-Discllaw") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.0, | |
| "tflops": 490.2053045046936, | |
| "token/s": 1736.022262942593, | |
| "train_loss": 0.035910474946516446, | |
| "train_runtime": 31598.4886, | |
| "train_samples_per_second": 6.603, | |
| "train_steps_per_second": 0.026 | |
| } |