Fill-Mask
Transformers
ONNX
Safetensors
Bashkir
bashkir-roberta-preln
bashkir
masked-language-modeling
roberta
sentencepiece
custom-code
onnxruntime
custom_code
Instructions to use failed09/bashkir-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use failed09/bashkir-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="failed09/bashkir-roberta", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("failed09/bashkir-roberta", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add quantized INT8 ONNX model export (58 MB)
Browse files- onnx/model_int8.onnx +3 -0
onnx/model_int8.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7826c5f46be23f17838c7c3478d24f6ea0e29ebe388cae92a102cb125d5b1c19
|
| 3 |
+
size 60916742
|