Instructions to use heitorrosa/logun-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use heitorrosa/logun-base with PEFT:
Task type is invalid.
- Transformers
How to use heitorrosa/logun-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="heitorrosa/logun-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("heitorrosa/logun-base") model = AutoModelForMaskedLM.from_pretrained("heitorrosa/logun-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Copy heitorrosa/logun-base/sft/checkpoint-1350/tokenizer_config.json to heitorrosa/logun-base/sft-0.5/checkpoint-1350/tokenizer_config.json
Browse files
sft-0.5/checkpoint-1350/tokenizer_config.json
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{
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"backend": "tokenizers",
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"bos_token": "[CLS]",
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"clean_up_tokenization_spaces": false,
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"eos_token": "[SEP]",
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"is_local": false,
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"local_files_only": false,
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"mask_token": "[MASK]",
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"model_input_names": [
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"input_ids",
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"attention_mask"
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],
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"model_max_length": 8192,
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"pad_token": "[PAD]",
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"padding_side": "right",
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"tokenizer_class": "TokenizersBackend",
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"truncation_side": "right",
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"unk_token": "[UNK]"
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}
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