Video-Text-to-Text
Transformers
Safetensors
molmo2
image-text-to-text
video
object-tracking
ecology
custom_code
Instructions to use tidalove/Molmo2Fish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tidalove/Molmo2Fish with Transformers:
# Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("tidalove/Molmo2Fish", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Raw training checkpoint (model + optimizer state) for step420
Browse files
Molmo2Fish-step420-raw.tar
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a3e8e49c04eebedc9fa3bd7a7baa710ecbc7fec934b527d17f7902d049f3fbfc
|
| 3 |
+
size 36971192320
|