Instructions to use MaagDeveloper/rust_python_roberta_base_mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaagDeveloper/rust_python_roberta_base_mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MaagDeveloper/rust_python_roberta_base_mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MaagDeveloper/rust_python_roberta_base_mlm") model = AutoModelForMaskedLM.from_pretrained("MaagDeveloper/rust_python_roberta_base_mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from MaagDeveloper/rust_python_roberta_base_mlm: direct link, hf CLI and curl.
- Browser
- Download file 340 Bytes
-
https://huggingface.co/MaagDeveloper/rust_python_roberta_base_mlm/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://MaagDeveloper/rust_python_roberta_base_mlm/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/MaagDeveloper/rust_python_roberta_base_mlm/resolve/main/tokenizer_config.json
340 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "eos_token": "</s>", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |