Instructions to use jinaai/xlm-roberta-flash-implementation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinaai/xlm-roberta-flash-implementation with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jinaai/xlm-roberta-flash-implementation", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Fixup post init (for v5 remot compatibility)
#60
by AntonV HF Staff - opened
- modeling_xlm_roberta.py +1 -0
modeling_xlm_roberta.py
CHANGED
|
@@ -480,6 +480,7 @@ class XLMRobertaModel(XLMRobertaPreTrainedModel):
|
|
| 480 |
self.name_or_path, trust_remote_code=True
|
| 481 |
)
|
| 482 |
self._rotary_emb_base = config.rotary_emb_base
|
|
|
|
| 483 |
|
| 484 |
@torch.inference_mode()
|
| 485 |
def encode(
|
|
|
|
| 480 |
self.name_or_path, trust_remote_code=True
|
| 481 |
)
|
| 482 |
self._rotary_emb_base = config.rotary_emb_base
|
| 483 |
+
self.post_init()
|
| 484 |
|
| 485 |
@torch.inference_mode()
|
| 486 |
def encode(
|