docs: write approximate timings as about instead of tilde

README.md

@@ -46,7 +46,7 @@ holds the LoRA only; the loader and examples live at
 | Adapter | PEFT LoRA, rank 256 / alpha 256, on attention, feed-forward and both time embedders (316 modules); 2.8 GB |
 | Sampling | 8 forward passes on a fixed sigma grid stored in the file (video shift 12, audio shift 3) |
 | Workflows | `t2va`, `fl2va` and `ref2va`, one file for all three (`ref2va` loads it onto `transformer_ref/`) |
-| Speed-up | ~3x end to end against the 49-NFE Diffusers baseline (~60 s vs ~175 s per clip on 4x H200) |
+| Speed-up | about 3x end to end against the 49-NFE Diffusers baseline (about 60 s vs about 175 s per clip on 4x H200) |
 | Optional | Ulysses context parallel on up to 4 GPUs; FlashAttention-3; NVIDIA Sol-Attn sparse attention |
 | License | [MiniMax H3 Community License Agreement](LICENSE); code on GitHub is Apache-2.0. See [License](#license) |
 
@@ -133,15 +133,15 @@ hyperflow-h3-fl2va --prompt "..." --image first.png --gpus 1   # the official si
 
 HyperFlow (8 NFE, 9 sigma points) against the base pipeline at Diffusers' default (49 NFE, 50 sigma points) on the
 same clip: `fl2va`, 124 frames, 1344x768, seed 0, dense SDPA attention. Pipeline time covers text encoding, denoising
-and decoding; process start-up and weight loading add ~30 s.
+and decoding; process start-up and weight loading add about 30 s.
 
 | | Base, 49 NFE | HyperFlow, 8 NFE | Speed-up |
 |---|---|---|---|
-| 4x H200, Ulysses degree 4 | ~175 s | ~60 s | 2.9x |
-| 1x H200, auto CPU offload | ~395 s | ~130 s | 3.0x |
+| 4x H200, Ulysses degree 4 | about 175 s | about 60 s | 2.9x |
+| 1x H200, auto CPU offload | about 395 s | about 130 s | 3.0x |
 
 The speed-up is below the 49:8 NFE ratio because text encoding and VAE decoding, which HyperFlow leaves unchanged,
-now take much of the run. Peak accelerator memory is ~80 GB per card either way (the LoRA adds 2.8 GB). The
+now take much of the run. Peak accelerator memory is about 80 GB per card either way (the LoRA adds 2.8 GB). The
 single-GPU row uses `memory_reserve_margin="24GB"`, not the official recipe's 12 GB: on a 141 GB H200 a smaller margin
 evicts the 10 GB VAE instead of the 62 GB text encoder when the DiT arrives and starves the denoiser. An 80 GB card
 is untested.
@@ -196,7 +196,7 @@ meta.base_model_revision, meta.sigmas, meta.gate
 
 ## Intended use and limitations
 
-- A drop-in speed-up for MiniMax-H3 inference on diffusers: same inputs, same outputs (video + stereo audio), ~3x
+- A drop-in speed-up for MiniMax-H3 inference on diffusers: same inputs, same outputs (video + stereo audio), about 3x
   faster end to end. It is a distilled few-step sampler, so compare against the base Diffusers pipeline on your own
   prompts before adopting it (`--baseline` in the example scripts runs both on the same seed).
 - Prompt following, languages, biases and failure modes are the base model's, which the distillation is designed to