Instructions to use hf-tiny-model-private/tiny-random-ReformerForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ReformerForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-ReformerForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ReformerForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-ReformerForMaskedLM") - Notebooks
- Google Colab
- Kaggle
| { | |
| "additional_special_tokens": [], | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "</s>", | |
| "model_max_length": 100, | |
| "sp_model_kwargs": {}, | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "ReformerTokenizer", | |
| "unk_token": "<unk>" | |
| } | |