Instructions to use HankyStyle/Multi-ling-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HankyStyle/Multi-ling-BERT with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="HankyStyle/Multi-ling-BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("HankyStyle/Multi-ling-BERT") model = AutoModelForQuestionAnswering.from_pretrained("HankyStyle/Multi-ling-BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit 路
61abc2f
1
Parent(s): a998163
Update README.md
Browse files
README.md
CHANGED
|
@@ -39,6 +39,6 @@ tokenizer.convert_ids_to_tokens(inputs["input_ids"][0])
|
|
| 39 |
|
| 40 |
|
| 41 |
tokenizer.decode(inputs["input_ids"][0])
|
| 42 |
-
[
|
| 43 |
|
| 44 |
```
|
|
|
|
| 39 |
|
| 40 |
|
| 41 |
tokenizer.decode(inputs["input_ids"][0])
|
| 42 |
+
{[CLS] i feel happy today! [SEP]}
|
| 43 |
|
| 44 |
```
|