Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use aisuko/ft-bert-base-uncased-for-binary-search with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aisuko/ft-bert-base-uncased-for-binary-search with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aisuko/ft-bert-base-uncased-for-binary-search")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aisuko/ft-bert-base-uncased-for-binary-search") model = AutoModelForSequenceClassification.from_pretrained("aisuko/ft-bert-base-uncased-for-binary-search", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files
README.md
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
---
|
|
|
|
| 2 |
library_name: transformers
|
| 3 |
license: apache-2.0
|
| 4 |
-
base_model: bert-base-uncased
|
| 5 |
tags:
|
| 6 |
- generated_from_trainer
|
| 7 |
model-index:
|
|
|
|
| 1 |
---
|
| 2 |
+
base_model: bert-base-uncased
|
| 3 |
library_name: transformers
|
| 4 |
license: apache-2.0
|
|
|
|
| 5 |
tags:
|
| 6 |
- generated_from_trainer
|
| 7 |
model-index:
|