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
File size: 424 Bytes
336ba04 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"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"
}
|