Instructions to use alphaedge-ai/mmBERT-base-deu-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mmBERT-base-deu-32768 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mmBERT-base-deu-32768")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mmBERT-base-deu-32768") model = AutoModel.from_pretrained("alphaedge-ai/mmBERT-base-deu-32768", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 380 Bytes
6b1a2e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"backend": "tokenizers",
"bos_token": "<bos>",
"cls_token": "<bos>",
"eos_token": "<eos>",
"mask_token": "<mask>",
"model_max_length": 8192,
"pad_token": "<pad>",
"padding_side": "right",
"sep_token": "<eos>",
"tokenizer_class": "TokenizersBackend",
"unk_token": "<unk>",
"model_input_names": [
"input_ids",
"attention_mask"
]
} |