Instructions to use insagur/n574a1c1a368c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use insagur/n574a1c1a368c with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("insagur/n574a1c1a368c", torch_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
Ctrl+K
- qwen-cua__runs__full_mixed_32k_fa2_prod_nopack__v0-20260529-115800__checkpoint-6694__evalweights
- qwen-cua__runs__ip2p_cu_desktop_nlonly__checkpoint-6000
- qwen-cua__runs__opencua_exact_wm_joint_v7_siglip2_delta_pad_pool32x32_phase2_baseline_wmonly_llmfrozen__v2-20260617-102530__checkpoint-4336
- qwen-cua__runs__probe_control500__v0-20260620-203711__checkpoint-500__evalweights
- qwen-cua__runs__qwen35_4b_planA_baseline-20260604-174400__v0-20260604-174503__checkpoint-436__evalweights
- qwen-cua__runs__qwen35_4b_planA_baseline_planning_12k-20260605-203833__v0-20260605-203901__checkpoint-1242__evalweights
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- 3.69 GB xet
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- 398 MB xet
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- 390 Bytes
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