Instructions to use lyleokoth/code-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lyleokoth/code-extraction with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/paligemma-3b-pt-224") model = PeftModel.from_pretrained(base_model, "lyleokoth/code-extraction") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 300
Browse files
adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 45258384
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:be2e388da8128d4e742b8c5694b4cca4f4d0f1ad850674a9d3b42802f0677443
|
| 3 |
size 45258384
|
runs/Jul05_14-42-06_e7ed27cc0a22/events.out.tfevents.1720190537.e7ed27cc0a22.270.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bf0b4d1e6b2972e6bba80242142ee73cea692f2c1f1483192903ecd4441d70d7
|
| 3 |
+
size 11999
|