Instructions to use fundthmcalculus/LFM2-350M-hugcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fundthmcalculus/LFM2-350M-hugcoder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/LFM2-350M") model = PeftModel.from_pretrained(base_model, "fundthmcalculus/LFM2-350M-hugcoder") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 100
Browse files
adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 95969208
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fcb8815ed2eb25e66868f4eb876ddfd1a335a3d2c442bd8217c61b0aeb5f7ced
|
| 3 |
size 95969208
|