Feature Extraction
Transformers
Safetensors
Russian
bert
fill-mask
custom_code
text-embeddings-inference
Instructions to use Tochka-AI/ruRoPEBert-e5-base-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tochka-AI/ruRoPEBert-e5-base-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Tochka-AI/ruRoPEBert-e5-base-512", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Tochka-AI/ruRoPEBert-e5-base-512", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("Tochka-AI/ruRoPEBert-e5-base-512", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -7,7 +7,7 @@ datasets:
|
|
| 7 |
- uonlp/CulturaX
|
| 8 |
---
|
| 9 |
|
| 10 |
-
# ruRoPEBert
|
| 11 |
|
| 12 |
This is an encoder model from **Tochka AI** based on the **RoPEBert** architecture, using the cloning method described in [our article on Habr](https://habr.com/ru/companies/tochka/articles/797561/).
|
| 13 |
|
|
@@ -89,5 +89,5 @@ Evaluation of this model on encodechka benchmark:
|
|
| 89 |
| intfloat/multilingual-e5-base | 0.834 | 0.704 | 0.458 | 0.795 | 0.964 | 0.782 | 0.803 | 0.740 | 0.234 | 0.373 | 0.76 | 0.668 |
|
| 90 |
|
| 91 |
## Authors
|
| 92 |
-
- Sergei Bratchikov (Tochka AI Team, [HF](https://huggingface.co/hivaze), [GitHub](https://
|
| 93 |
- Maxim Afanasiev (Tochka AI Team, [HF](https://huggingface.co/mrapplexz), [GitHub](https://github.com/mrapplexz))
|
|
|
|
| 7 |
- uonlp/CulturaX
|
| 8 |
---
|
| 9 |
|
| 10 |
+
# ruRoPEBert Sentence Model for Russian language
|
| 11 |
|
| 12 |
This is an encoder model from **Tochka AI** based on the **RoPEBert** architecture, using the cloning method described in [our article on Habr](https://habr.com/ru/companies/tochka/articles/797561/).
|
| 13 |
|
|
|
|
| 89 |
| intfloat/multilingual-e5-base | 0.834 | 0.704 | 0.458 | 0.795 | 0.964 | 0.782 | 0.803 | 0.740 | 0.234 | 0.373 | 0.76 | 0.668 |
|
| 90 |
|
| 91 |
## Authors
|
| 92 |
+
- Sergei Bratchikov (Tochka AI Team, [HF](https://huggingface.co/hivaze), [GitHub](https://github.com/hivaze))
|
| 93 |
- Maxim Afanasiev (Tochka AI Team, [HF](https://huggingface.co/mrapplexz), [GitHub](https://github.com/mrapplexz))
|