Instructions to use rohitnagareddy/gemma-2b-python-expert-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rohitnagareddy/gemma-2b-python-expert-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "rohitnagareddy/gemma-2b-python-expert-lora") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -12,7 +12,7 @@ tags:
|
|
| 12 |
library_name: peft
|
| 13 |
---
|
| 14 |
|
| 15 |
-
# gemma-2b-python-expert-lora
|
| 16 |
|
| 17 |
This LoRA adapter specializes the base model for expert-level Python programming. Created using Sakana AI's Text-to-LoRA technology.
|
| 18 |
|
|
|
|
| 12 |
library_name: peft
|
| 13 |
---
|
| 14 |
|
| 15 |
+
# gemma-2b-python-expert-lora(Text to Model)
|
| 16 |
|
| 17 |
This LoRA adapter specializes the base model for expert-level Python programming. Created using Sakana AI's Text-to-LoRA technology.
|
| 18 |
|