Instructions to use formermagic/roberta-base-python-1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use formermagic/roberta-base-python-1m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="formermagic/roberta-base-python-1m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("formermagic/roberta-base-python-1m") model = AutoModelForMaskedLM.from_pretrained("formermagic/roberta-base-python-1m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from formermagic/roberta-base-python-1m: direct link, hf CLI and curl.
- Browser
- Download file 265 Bytes
-
https://huggingface.co/formermagic/roberta-base-python-1m/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://formermagic/roberta-base-python-1m/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/formermagic/roberta-base-python-1m/resolve/main/tokenizer_config.json
265 Bytes
| {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "add_prefix_space": false, "errors": "replace", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "trim_offsets": true, "lowercase": false, "model_max_length": 512} |