Any-to-Any
Safetensors
Transformers
LongCat-Next
longcat_next
text-generation
multimodal
custom_code
Instructions to use Artificial-Production-Units/LongCat-Next with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Artificial-Production-Units/LongCat-Next with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Artificial-Production-Units/LongCat-Next", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from Artificial-Production-Units/LongCat-Next: direct link, hf CLI and curl.
- Browser
- Download file 408 Bytes
-
https://huggingface.co/Artificial-Production-Units/LongCat-Next/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://Artificial-Production-Units/LongCat-Next/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Artificial-Production-Units/LongCat-Next/resolve/main/preprocessor_config.json
408 Bytes
| { | |
| "processor_class": "LongcatNextProcessor", | |
| "auto_map": { | |
| "AutoProcessor": "processing_longcat_next.LongcatNextProcessor" | |
| }, | |
| "spatial_merge_size": 2, | |
| "max_pixels": 3211264, | |
| "min_pixels": 50176, | |
| "n_fft": 400, | |
| "num_mel_bins": 128, | |
| "sampling_rate": 16000, | |
| "max_audio_seconds": 30, | |
| "hop_length": 160, | |
| "kernel_size": 3, | |
| "stride_size": 2, | |
| "split_overlap": 0.0, | |
| "avg_pooler": 4 | |
| } |