详情
推荐
flux1-dev_8x8_scaled
flux.1_dev_8x8
flux.1_dev_fp8_fp16t5
flux.1_dev_16x16
flux.1_schnell_8x8
flux.1_schnell_fp8_fp16t5
flux.1_schnell_16x16
marduk191's Flux.1 collection

marduk191's Flux.1 collection

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#模型
#工具
#工具
#chekpoint
#通量.1
#flux1.d
#flux1.年代
#Fluxl

I compiled a little collection of flux.1 models. there are fp8 models with fp8 t5 and fp8 models with fp16 t5 for both dev and schnell. Single files for use with the regular checkpoint loader. there are also fp16 models available now. all models have clip, t5, and vae baked in. THESE ARE ALL STOCK FLUX.1

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These all use bf16 upcasting, use the appropriate flags if you are tuning on gtx cards for some reason.

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Unified single file versions of flux.1 for comfyui. All files have a baked in VAE and clip L included:

flux.1_dev_8x8_e4m3fn-marduk191.safetensors is Flux.1 Dev quantized to 8 bit with an 8 bit T5 XXL encoder included.

flux.1_dev_fp8_fp16t5-marduk191.safetensors is Flux.1 Dev quantized to 8 bit with an 16 bit T5 XXL encoder included.

flux.1_schnell_8x8_e4m3fn-marduk191.safetensors is Flux.1 Schnell quantized to 8 bit with an 8 bit T5 XXL encoder included.

flux.1_schnell_fp8_fp16t5-marduk191.safetensors is Flux.1 Schnell quantized to 8 bit with an 16 bit T5 XXL encoder included.

flux.1_dev_16x16-marduk191.safetensors Flux.1 Dev quantized to 16 bit with an 16 bit T5 XXL encoder included.

flux.1_schnell_16x16-marduk191.safetensors Flux.1 Schnell quantized to 16 bit with an 16 bit T5 XXL encoder included.

flux.1_dev_8x8_scaled-marduk191.safetensors is Flux.1 Dev quantized to 8 bit scaled stochastic weights and normalized outlaying alphas. It uses an 8 bit scale dstochastic (tag limited to avoid loss) T5 XXL encoder included.

Workflow examples are available here: SOON

Repository is here: https://huggingface.co/marduk191/Flux.1_collection/tree/main

Discord: https://discord.gg/s3kj9VqpKc

Tips welcome: https://ko-fi.com/marduk191

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公告
2024-08-12
发布模型
2025-06-04
更新模型信息
模型详情
类型
Checkpoint
发布时间
2025-06-04
基础模型
Flux.1 D
版本介绍

Added flux1-dev_8x8_scaled. both unet and t5 are converted to fp8 scaled weights and should be a sweet spot. This replaces fp16 static weights if i didn't mess up the alphas lol. I am pretty sure it worked out.

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来源: civitai

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