Instructions to use ibm-research/re2g-reranker-triviaqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/re2g-reranker-triviaqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ibm-research/re2g-reranker-triviaqa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ibm-research/re2g-reranker-triviaqa") model = AutoModelForSequenceClassification.from_pretrained("ibm-research/re2g-reranker-triviaqa") - Notebooks
- Google Colab
- Kaggle
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tokenizer_config.json
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{"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "max_len": 512, "special_tokens_map_file": "/root/.cache/huggingface/transformers/4d0fa11bbe1deb7997febb2e52bd0163cbe96e544e88da5610c4c2517ca7386f.60fcb958324e8baca172b9bf464ef31dd71d694d16137059005be28205a96366", "tokenizer_file": null, "name_or_path": "/data/KILT/qa/triviaqa/models/reranker_stage1"}
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