Instructions to use alienit/query-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alienit/query-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="alienit/query-bert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("alienit/query-bert") model = AutoModel.from_pretrained("alienit/query-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: fa | |
| tags: | |
| - exbert | |
| license: apache-2.0 | |
| datasets: | |
| - parsQuAD | |
| ### Inroduction | |
| This model is finetuned from [parsbert](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased). | |
| ### How to use | |
| ```python | |
| from transformers import AutoConfig, AutoTokenizer, AutoModel | |
| model_name = "alienit/query-bert" | |
| config = AutoConfig.from_pretrained(model_name) | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModel.from_pretrained(model_name) | |
| text = "چرا انسانها موجودات اجتماعی هستند؟" | |
| encoded_input = tokenizer(text, return_tensors='pt') | |
| output = model(**encoded_input) | |
| ``` |