Text Classification
Transformers
Safetensors
themis_vl
feature-extraction
themis
decision-model
structured-prediction
probabilities
multimodal
vision-language
custom_code
lora
Instructions to use lothnic/themis-vl-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lothnic/themis-vl-2b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lothnic/themis-vl-2b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lothnic/themis-vl-2b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from lothnic/themis-vl-2b: direct link, hf CLI and curl.
- Browser
- Download file 443 Bytes
-
https://huggingface.co/lothnic/themis-vl-2b/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://lothnic/themis-vl-2b/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/lothnic/themis-vl-2b/resolve/main/preprocessor_config.json
443 Bytes
| { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Qwen2VLImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "merge_size": 2, | |
| "patch_size": 16, | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 16777216, | |
| "shortest_edge": 65536 | |
| }, | |
| "temporal_patch_size": 2 | |
| } | |