Fill-Mask
Transformers
Safetensors
English
ultrabert
encoder
masked-language-modeling
long-context
custom_code
Instructions to use dmis-lab/UltraBERT-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmis-lab/UltraBERT-150M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dmis-lab/UltraBERT-150M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dmis-lab/UltraBERT-150M", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("dmis-lab/UltraBERT-150M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from dmis-lab/UltraBERT-150M: direct link, hf CLI and curl.
- Browser
- Download file 765 Bytes
-
https://huggingface.co/dmis-lab/UltraBERT-150M/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://dmis-lab/UltraBERT-150M/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/dmis-lab/UltraBERT-150M/resolve/main/tokenizer_config.json
765 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|endoftext|>", | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<repo_name>", | |
| "<reponame>", | |
| "<file_sep>", | |
| "<filename>", | |
| "<gh_stars>", | |
| "<issue_start>", | |
| "<issue_comment>", | |
| "<issue_closed>", | |
| "<jupyter_start>", | |
| "<jupyter_text>", | |
| "<jupyter_code>", | |
| "<jupyter_output>", | |
| "<|sep|>", | |
| "<|mask|>" | |
| ], | |
| "mask_token": "<|mask|>", | |
| "model_max_length": 32768, | |
| "pad_token": "<|endoftext|>", | |
| "sep_token": "<|sep|>", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>", | |
| "vocab_size": 49152 | |
| } | |