Instructions to use bilbo991/clip-mixer-300k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bilbo991/clip-mixer-300k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bilbo991/clip-mixer-300k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("bilbo991/clip-mixer-300k") model = AutoModel.from_pretrained("bilbo991/clip-mixer-300k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 892012613
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d32d9047a16070c5404c04d4c08fd988ec48cc89f8b35e97a5b128d223ab974f
|
| 3 |
size 892012613
|
runs/Aug16_14-43-59_cvrl-flynn-ws2/events.out.tfevents.1692211514.cvrl-flynn-ws2.10527.0
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:b88e8c773c4811d086f32770b5e9de72fcd435cd3d0d8cb845f362674144afb2
|
| 3 |
+
size 17761
|