Instructions to use Ananthusajeev190/NanoTok with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ananthusajeev190/NanoTok with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Ananthusajeev190/NanoTok", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Bun AI π₯
Bun AI is a lightweight, low-resource AI model designed for mobile and low-end devices.
Features
- β Under 100MB safetensors
- β INT8 quantized
- β Google Colab trained
- β Mobile-friendly
- β Open & minimal
Files
bun_model.safetensorsβ model weightsvocab.jsonβ tokenizer vocabularytokenizer_config.jsonβ tokenizer settingsspecial_tokens_map.jsonβ special tokens
Intended Use
- Education
- Experiments
- Edge devices
- Offline inference
Limitations
This is a small model and not suitable for high-accuracy tasks.
License
MIT
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