Instructions to use jason1966/CoPaw-Flash-9B-DataAnalyst-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jason1966/CoPaw-Flash-9B-DataAnalyst-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/shadeform/CoPaw-Flash-9B") model = PeftModel.from_pretrained(base_model, "jason1966/CoPaw-Flash-9B-DataAnalyst-LoRA") - Notebooks
- Google Colab
- Kaggle
Upload benchmark-chart.png
Browse files- .gitattributes +1 -0
- benchmark-chart.png +3 -0
.gitattributes
CHANGED
|
@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
.ipynb_checkpoints/dataanalyst-demo-checkpoint.gif filter=lfs diff=lfs merge=lfs -text
|
| 37 |
dataanalyst-demo.gif filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
.ipynb_checkpoints/dataanalyst-demo-checkpoint.gif filter=lfs diff=lfs merge=lfs -text
|
| 37 |
dataanalyst-demo.gif filter=lfs diff=lfs merge=lfs -text
|
| 38 |
+
benchmark-chart.png filter=lfs diff=lfs merge=lfs -text
|
benchmark-chart.png
ADDED
|
Git LFS Details
|