Feature Extraction
Transformers
Safetensors
multilingual
neomme
multimodal
document-understanding
masked-language-modeling
long-context
Instructions to use Hcompany/NeoMME-800M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hcompany/NeoMME-800M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Hcompany/NeoMME-800M")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Hcompany/NeoMME-800M") model = AutoModel.from_pretrained("Hcompany/NeoMME-800M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from Hcompany/NeoMME-800M: direct link, hf CLI and curl.
- Browser
- Download file 424 Bytes
-
https://huggingface.co/Hcompany/NeoMME-800M/resolve/main/processor_config.json
- Command line
-
hf download hf://Hcompany/NeoMME-800M/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/Hcompany/NeoMME-800M/resolve/main/processor_config.json
424 Bytes
| { | |
| "image_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "NeoMMEImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "patch_size": 32, | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098 | |
| }, | |
| "processor_class": "NeoMMEProcessor" | |
| } | |