README: drop ~ prefix (was rendering as strikethrough on Hub)

README.md

@@ -37,17 +37,17 @@ configs:
 
 ## Description
 
-> **~173M DNA & RNA sequences · ~1.1 trillion nucleotides** — the DNA pretraining mixture used to train [Carbon](https://github.com/huggingface/carbon), a genomic foundation model.
+> **173M DNA & RNA sequences · 1.1 trillion nucleotides** — the DNA pretraining mixture used to train [Carbon](https://github.com/huggingface/carbon), a genomic foundation model.
 
 This dataset is a collection of data sources intended for training genomic foundation models, such as Carbon. It contains DNA and RNA sequences spanning eukaryote and prokaryote species.
-Across the four main configs it totals ~1.1 T DNA base pairs (~180B tokens with Carbon's 6-mer tokenizer). A pre-sampled 10B-token eukaryote subset (`eukaryote_generator_10B_subset`) is also provided for smaller / faster runs.
+Across the four main configs it totals 1.1 T DNA base pairs (180B tokens with Carbon's 6-mer tokenizer). A pre-sampled 10B-token eukaryote subset (`eukaryote_generator_10B_subset`) is also provided for smaller / faster runs.
 
 | Subset | Domain | Source | Size | Rows | Nucleotides |
 |---|---|---|---:|---:|---:|
-| `eukaryote_generator` | Eukaryote genomes (≤ 100 kbp) | GenerTeam / GENERATOR | 191.9 GB | 46,323,396 | ~423.4 Gbp |
-| `mrna_evo2` | Messenger RNA | Arc Institute / OpenGenome2 | 54.8 GB | 52,702,454 | ~115.9 Gbp |
-| `mrna_splice_evo2` | mRNA + splice & promoter | Arc Institute / OpenGenome2 | 92.9 GB | 56,877,762 | ~197.4 Gbp |
-| `prokaryote_evo2` | Prokaryote genomes (GTDB + IMG/PR) | Arc Institute / OpenGenome2 | 166.0 GB | 17,408,059 | ~357.5 Gbp |
+| `eukaryote_generator` | Eukaryote genomes (≤ 100 kbp) | GenerTeam / GENERATOR | 191.9 GB | 46,323,396 | 423.4 Gbp |
+| `mrna_evo2` | Messenger RNA | Arc Institute / OpenGenome2 | 54.8 GB | 52,702,454 | 115.9 Gbp |
+| `mrna_splice_evo2` | mRNA + splice & promoter | Arc Institute / OpenGenome2 | 92.9 GB | 56,877,762 | 197.4 Gbp |
+| `prokaryote_evo2` | Prokaryote genomes (GTDB + IMG/PR) | Arc Institute / OpenGenome2 | 166.0 GB | 17,408,059 | 357.5 Gbp |
 | `eukaryote_generator_10B_subset` | Eukaryote subsample (10B tokens, natural species distribution) | derived from `eukaryote_generator` | 27.6 GB | 6,562,876 | 60.0 Gbp |
 
 Nucleotides are counted in base pairs (Gbp = billion nucleotides). 
@@ -136,13 +136,13 @@ Sequences here are systematically longer than `mrna_evo2` — the extra promoter
 
 **Upstream:** [arcinstitute/opengenome2](https://huggingface.co/datasets/arcinstitute/opengenome2) (`gtdb_v220_imgpr` split)
 
-Long chromosomal chunks from bacteria and archaea, sourced from [GTDB v220](https://gtdb.ecogenomic.org/) (a curated taxonomy of ~85 K prokaryote genomes) and [IMG/PR](https://img.jgi.doe.gov/) (a DOE database of environmental prokaryote sequences). Prokaryote genomes are compact — genes sit back-to-back with minimal intergenic space — so these sequences are biologically rich per nucleotide.
+Long chromosomal chunks from bacteria and archaea, sourced from [GTDB v220](https://gtdb.ecogenomic.org/) (a curated taxonomy of 85 K prokaryote genomes) and [IMG/PR](https://img.jgi.doe.gov/) (a DOE database of environmental prokaryote sequences). Prokaryote genomes are compact — genes sit back-to-back with minimal intergenic space — so these sequences are biologically rich per nucleotide.
 
 ### 5. `eukaryote_generator_10B_subset` — 10B-token eukaryote subsample
 
 **Source:** derived from `eukaryote_generator` (this dataset).
 
-A pre-sampled subset of `eukaryote_generator` totalling ~60 Gbp (~10 B tokens at 6-mer tokenization) for smaller / faster model trainings that don't need the full 423 Gbp eukaryote slice. Rows are uniformly sampled at the row level from the filtered eukaryote data, which keeps the species distribution proportional to the natural per-species base-pair count:
+A pre-sampled subset of `eukaryote_generator` totalling 60 Gbp (10 B tokens at 6-mer tokenization) for smaller / faster model trainings that don't need the full 423 Gbp eukaryote slice. Rows are uniformly sampled at the row level from the filtered eukaryote data, which keeps the species distribution proportional to the natural per-species base-pair count:
 
 | Species | Natural share | In subset |
 |---|---:|---:|
@@ -164,10 +164,10 @@ The proportions below reflect the target mixture for Carbon's pure-DNA pretraini
 
 | Subset | Approx. weight |
 |---|---:|
-| `eukaryote_generator` | ~70% |
-| `mrna_evo2` | ~16% |
-| `prokaryote_evo2` | ~10% |
-| `mrna_splice_evo2` | ~4% |
+| `eukaryote_generator` | 70% |
+| `mrna_evo2` | 16% |
+| `prokaryote_evo2` | 10% |
+| `mrna_splice_evo2` | 4% |
 
 
 ### Metadata conditioning in Carbon training (`eukaryote_generator` only)