Sulphur-2-base-GGUF

Abiray/Sulphur-2-base-GGUF

Sulphur-2-base-GGUF is a text-to-video model from Abiray. Use it when you need video from a text prompt. It is set up for gguf.

This repository contains GGUF format model files for SulphurAI's Sulphur-2-base.

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From the Hugging Face model README

This repository contains GGUF format model files for SulphurAI's Sulphur-2-base.

The following quantization tiers are provided to accommodate different hardware capabilities and VRAM constraints.

Filename	Quantization Type	Size	Recommended Use
`sulphur_dev_bf16.gguf`	BF16 (16-bit)	42.0 GB	Unquantized baseline. Maximum quality and accuracy. Requires massive VRAM.
`sulphur_dev-Q8_0.gguf`	Q8_0 (8-bit)	22.8 GB	Extremely high quality, near unquantized performance.
`sulphur_dev-Q6_K.gguf`	Q6_K (6-bit)	17.8 GB	Very high quality, minimal precision loss.
`sulphur_dev-Q5_K_M.gguf`	Q5_K_M (5-bit)	16.1 GB	Excellent balance of quality and performance.
`sulphur_dev-Q5_K_S.gguf`	Q5_K_S (5-bit)	15.0 GB	Slightly smaller 5-bit variant for strict memory limits.
`sulphur_dev-Q4_K_M.gguf`	Q4_K_M (4-bit)	14.3 GB	Recommended standard. Fast inference with very low quality degradation.
`sulphur_dev-Q4_K_S.gguf`	Q4_K_S (4-bit)	13.2 GB	Smaller 4-bit variant, slightly lower quality than K_M.
`sulphur_dev-Q4_0.gguf`	Q4_0 (4-bit)	13.0 GB	Legacy 4-bit quant. Very fast inference but higher perplexity than K-quants.
`sulphur_dev-Q3_K_M.gguf`	Q3_K_M (3-bit)	11.1 GB	High compression. Best for constrained environments with limited RAM/VRAM.
`sulphur_dev-Q3_K_S.gguf`	Q3_K_S (3-bit)	10.3 GB	Maximum compression. Lowest footprint but highest quality loss.