Instructions to use oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned") model = AutoModelForQuestionAnswering.from_pretrained("oguzhanolm/loodos-bert-base-uncased-QA-fine-tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": "/root/.cache/huggingface/transformers/6d007a58d6b079f60f591e5187c9bb270778e6650fb2921f9879d9274a560862.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "loodos/bert-base-turkish-uncased", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |