Text Classification
Transformers
Safetensors
English
mistral3
image-text-to-text
decision-model
typed-decisions
schema-head
jev
calibration
decode-free
Instructions to use StandardThinking/StandardOne-3B-SH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StandardThinking/StandardOne-3B-SH with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StandardThinking/StandardOne-3B-SH")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("StandardThinking/StandardOne-3B-SH") model = AutoModelForMultimodalLM.from_pretrained("StandardThinking/StandardOne-3B-SH", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tekken.json from StandardThinking/StandardOne-3B-SH: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/StandardThinking/StandardOne-3B-SH/resolve/main/tekken.json
- Command line
-
hf download hf://StandardThinking/StandardOne-3B-SH/tekken.json
-
curl -L -o tekken.json https://huggingface.co/StandardThinking/StandardOne-3B-SH/resolve/main/tekken.json
16.8 MB
- Xet hash:
- 2eb4e432a16f4da976f1ec496cc0036c13302a0402457bdf6af61f3639c46c98
- Size of remote file:
- 16.8 MB
- SHA256:
- 600bb27946565481ecf51ba8aee252e49b9a68507866080ac9c30185bb312843
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.