Instructions to use uer/chinese_roberta_L-8_H-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uer/chinese_roberta_L-8_H-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uer/chinese_roberta_L-8_H-256")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uer/chinese_roberta_L-8_H-256") model = AutoModelForMaskedLM.from_pretrained("uer/chinese_roberta_L-8_H-256") - Notebooks
- Google Colab
- Kaggle
Commit ·
76009ef
1
Parent(s): 54ed33f
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:430ce5f230d841135b73b251864315226d9357810df58ea558a0685801dae8cb
|
| 3 |
+
size 47790497
|