Zero-Shot Classification
Transformers
Safetensors
MLX
English
qwen3_5
image-text-to-text
decision-model
calibration
teximal
fort
Instructions to use teximal/fort-1-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use teximal/fort-1-2b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="teximal/fort-1-2b")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("teximal/fort-1-2b") model = AutoModelForMultimodalLM.from_pretrained("teximal/fort-1-2b", device_map="auto") - MLX
How to use teximal/fort-1-2b with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download teximal/fort-1-2b --local-dir fort-1-2b
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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