Instructions to use BAAI/Emu3-Stage1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/Emu3-Stage1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("BAAI/Emu3-Stage1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from BAAI/Emu3-Stage1: direct link, hf CLI and curl.
- Browser
- Download file 364 Bytes
-
https://huggingface.co/BAAI/Emu3-Stage1/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://BAAI/Emu3-Stage1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/BAAI/Emu3-Stage1/resolve/main/tokenizer_config.json
364 Bytes
| { | |
| "added_tokens_decoder": {}, | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_emu3.Emu3Tokenizer", | |
| null | |
| ] | |
| }, | |
| "bos_token": "<|extra_203|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|extra_204|>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|endoftext|>", | |
| "tokenizer_class": "Emu3Tokenizer" | |
| } | |