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
Download tokenizer_config.json from heitorrosa/logun-base: direct link, hf CLI and curl.
- Browser
- Download file 457 Bytes
-
https://huggingface.co/heitorrosa/logun-base/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://heitorrosa/logun-base/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/heitorrosa/logun-base/resolve/main/tokenizer_config.json
457 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "[CLS]", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "[SEP]", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 8192, | |
| "pad_token": "[PAD]", | |
| "padding_side": "right", | |
| "tokenizer_class": "TokenizersBackend", | |
| "truncation_side": "right", | |
| "unk_token": "[UNK]" | |
| } | |