Instructions to use albert/albert-xlarge-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-xlarge-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-xlarge-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-xlarge-v1") model = AutoModelForMaskedLM.from_pretrained("albert/albert-xlarge-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adds the tokenizer configuration file (#2)
Verified signature- Adds tokenizer_config.json file (3951a216abd0d15e056a9066c9a2adbe73e03e35)ed6f87d
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (d27456aedbb886136ced8326523680b3dd7d7e80) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>e9b59db
-
Large -> Xlarge
a74dd20 -
Copy model card from albert-large-v1
9fcd16f
-
For clarity, delete deprecated modelcard.json
We now use the README.md model card instead Approved-by: Julien Chaumond <julien@huggingface.co>16cd5fd
-
Update tokenizer.json
768a09f
-
Update tokenizer.json
508666f
-
Update tf_model.h5
28c1d97
-
Update config.json
a2abb28
-
Update spiece.model
dd69912 -
Update config.json
cc32f38 -
Update pytorch_model.bin
ab53634
-
Update with-prefix-tf_model.h5
f9d03ff
-
Update modelcard.json
33d178c -
initial commit
f40a6f5