Instructions to use jaimin/Bullet_Point with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaimin/Bullet_Point with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="jaimin/Bullet_Point")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("jaimin/Bullet_Point") model = AutoModelForQuestionAnswering.from_pretrained("jaimin/Bullet_Point") - Notebooks
- Google Colab
- Kaggle
Upload 2 files
Browse files- rust_model.ot +3 -0
- special_tokens_map.json +1 -0
rust_model.ot
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version https://git-lfs.github.com/spec/v1
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oid sha256:5a16ed126bbc8c4cf794406bac0c7946f62d0f175c02dc54d77a00a6255597ed
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special_tokens_map.json
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{"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "sep_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "cls_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}}
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