Feature Extraction
Transformers
Safetensors
English
modernbert
Generated from Trainer
custom_code
text-embeddings-inference
Instructions to use GliteTech/DisambertSingleSense-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GliteTech/DisambertSingleSense-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="GliteTech/DisambertSingleSense-base", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("GliteTech/DisambertSingleSense-base", trust_remote_code=True) model = AutoModel.from_pretrained("GliteTech/DisambertSingleSense-base", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Upload DisamBertSingleSense
Browse files- DisamBertSingleSense.py +3 -0
- model.safetensors +1 -1
DisamBertSingleSense.py
CHANGED
|
@@ -132,3 +132,6 @@ class DisamBertSingleSense(PreTrainedModel):
|
|
| 132 |
hidden_states=base_model_output.hidden_states if output_hidden_states else None,
|
| 133 |
attentions=base_model_output.attentions if output_attentions else None,
|
| 134 |
)
|
|
|
|
|
|
|
|
|
|
|
|
| 132 |
hidden_states=base_model_output.hidden_states if output_hidden_states else None,
|
| 133 |
attentions=base_model_output.attentions if output_attentions else None,
|
| 134 |
)
|
| 135 |
+
|
| 136 |
+
def get_input_embeddings(self):
|
| 137 |
+
return self.BaseModel.get_input_embeddings()
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 957996876
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:29b37d70127cb41266c8a6b4ddd50d910e208364a76db5e0d6c1a23cd2f4e0a4
|
| 3 |
size 957996876
|