Instructions to use radna/mini_intern_chat_triton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radna/mini_intern_chat_triton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="radna/mini_intern_chat_triton", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radna/mini_intern_chat_triton", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 469 Bytes
43533c4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"</box>": 32019,
"</img>": 32012,
"</quad>": 32015,
"</ref>": 32017,
"<IMG_CONTEXT>": 32013,
"<box>": 32018,
"<img>": 32011,
"<quad>": 32014,
"<ref>": 32016,
"<|assistant|>": 32001,
"<|endoftext|>": 32000,
"<|end|>": 32007,
"<|placeholder1|>": 32002,
"<|placeholder2|>": 32003,
"<|placeholder3|>": 32004,
"<|placeholder4|>": 32005,
"<|placeholder5|>": 32008,
"<|placeholder6|>": 32009,
"<|system|>": 32006,
"<|user|>": 32010
}
|