PEFT
TensorBoard
Safetensors
gemma
alignment-handbook
trl
sft
Generated from Trainer
4-bit precision
bitsandbytes
Instructions to use chansung/coding_llamaduo_60k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chansung/coding_llamaduo_60k with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-7b") model = PeftModel.from_pretrained(base_model, "chansung/coding_llamaduo_60k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 263ccf0eda97738e8c2c30ced588ef64a2ad2c40b89e48e97dc7e5c3e74cdb67
- Size of remote file:
- 17.5 MB
- SHA256:
- 322a5f52ab5cab196761ab397a022d6fa3a2e1418585e532bb6efb2fedd2ae94
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