Instructions to use ahmeshaf/ecb_tagger_seq2seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmeshaf/ecb_tagger_seq2seq with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ahmeshaf/ecb_tagger_seq2seq") model = AutoModelForSeq2SeqLM.from_pretrained("ahmeshaf/ecb_tagger_seq2seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -42,7 +42,7 @@ print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
|
|
| 42 |
|
| 43 |
```python
|
| 44 |
from transformers import pipeline
|
| 45 |
-
srl = pipeline("ahmeshaf/ecb_tagger_seq2seq")
|
| 46 |
print(srl(["I like this model and hate this sentence ."]))
|
| 47 |
|
| 48 |
# [{'generated_text': 'like | hate'}]
|
|
|
|
| 42 |
|
| 43 |
```python
|
| 44 |
from transformers import pipeline
|
| 45 |
+
srl = pipeline("text2text-generation", "ahmeshaf/ecb_tagger_seq2seq")
|
| 46 |
print(srl(["I like this model and hate this sentence ."]))
|
| 47 |
|
| 48 |
# [{'generated_text': 'like | hate'}]
|