Instructions to use Fduv/DeciCoder-FineTuned-CodeAlpaca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Fduv/DeciCoder-FineTuned-CodeAlpaca with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Deci/DeciCoder-1b") model = PeftModel.from_pretrained(base_model, "Fduv/DeciCoder-FineTuned-CodeAlpaca") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -36,7 +36,7 @@ The following `bitsandbytes` quantization config was used during training:
|
|
| 36 |
|
| 37 |
- PEFT 0.5.0
|
| 38 |
|
| 39 |
-
##
|
| 40 |
Thanks for DeciCoder-1b team for making this model open sourced.
|
| 41 |
```
|
| 42 |
@misc{DeciFoundationModels,
|
|
|
|
| 36 |
|
| 37 |
- PEFT 0.5.0
|
| 38 |
|
| 39 |
+
## Citation
|
| 40 |
Thanks for DeciCoder-1b team for making this model open sourced.
|
| 41 |
```
|
| 42 |
@misc{DeciFoundationModels,
|