Instructions to use deepmind/language-perceiver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepmind/language-perceiver with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="deepmind/language-perceiver")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("deepmind/language-perceiver") model = AutoModelForMaskedLM.from_pretrained("deepmind/language-perceiver") - Notebooks
- Google Colab
- Kaggle
Add file
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0a1032073589b0f153515d927d7871f3919d19aac7e79b37f278afdcda0fb642
|
| 3 |
+
size 804615471
|