Instructions to use deepmind/vision-perceiver-learned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepmind/vision-perceiver-learned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="deepmind/vision-perceiver-learned") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoTokenizer, AutoModelForImageClassification tokenizer = AutoTokenizer.from_pretrained("deepmind/vision-perceiver-learned") model = AutoModelForImageClassification.from_pretrained("deepmind/vision-perceiver-learned") - Notebooks
- Google Colab
- Kaggle
Update PyTorch model
Browse files- config.json +4 -0
- pytorch_model.bin +2 -2
config.json
CHANGED
|
@@ -2025,6 +2025,10 @@
|
|
| 2025 |
"self_attention_widening_factor": 1,
|
| 2026 |
"seq_len": 2048,
|
| 2027 |
"torch_dtype": "float32",
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2028 |
"transformers_version": "4.11.0.dev0",
|
| 2029 |
"use_query_residual": true,
|
| 2030 |
"v_channels": null,
|
|
|
|
| 2025 |
"self_attention_widening_factor": 1,
|
| 2026 |
"seq_len": 2048,
|
| 2027 |
"torch_dtype": "float32",
|
| 2028 |
+
"train_size": [
|
| 2029 |
+
368,
|
| 2030 |
+
496
|
| 2031 |
+
],
|
| 2032 |
"transformers_version": "4.11.0.dev0",
|
| 2033 |
"use_query_residual": true,
|
| 2034 |
"v_channels": null,
|
pytorch_model.bin
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 sha256:8c70524d5ed3b922f125b9bd84515a3190aa6e284da84009253917640a7acc1e
|
| 3 |
+
size 249079335
|