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-8B-SH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StandardThinking/StandardOne-8B-SH with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StandardThinking/StandardOne-8B-SH")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("StandardThinking/StandardOne-8B-SH") model = AutoModelForMultimodalLM.from_pretrained("StandardThinking/StandardOne-8B-SH", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download code/requirements.txt from StandardThinking/StandardOne-8B-SH: direct link, hf CLI and curl.
- Browser
- Download file 57 Bytes
-
https://huggingface.co/StandardThinking/StandardOne-8B-SH/resolve/main/code/requirements.txt
- Command line
-
hf download hf://StandardThinking/StandardOne-8B-SH/code/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/StandardThinking/StandardOne-8B-SH/resolve/main/code/requirements.txt
57 Bytes
| torch>=2.4 | |
| transformers==5.12.1 | |
| peft==0.21.0 | |
| safetensors | |