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Open-weight model · Text generation
by Francesca Padovani francesca9805/isl-100mb-after-wc-zipf-newlex-before-ckpt500-packed-bfdiso_seed455
isl-100mb-after-wc-zipf-newlex-before-ckpt500-packed-bfdiso_seed455 is an open-weight model for text generation from Francesca Padovani. It has 125M parameters. At 16-bit it needs about 0.3 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
This model is a fine-tuned version of francesca9805/ppt-wc-zipf-newlex-isl-before-100mb-packed-bfdisoseed455. It has been trained using TRL. This model was trained with SFT.
What it takes to serve isl-100mb-after-wc-zipf-newlex-before-ckpt500-packed-bfdiso_seed455 (125M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 0.2 GB | 0.3 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.1 GB | 0.1 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.1 GB | 0.1 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 20, 2026.
This model is a fine-tuned version of francesca9805/ppt-wc-zipf-newlex-isl-before-100mb-packed-bfdisoseed455. It has been trained using TRL. This model was trained with SFT.
Excerpt from the card by Francesca Padovani.
39 files, 1.0 GB in total. The weights are 11 files totalling 998.3 MB in bin, pth, safetensors.
| File | Type | Size | SHA-256 |
|---|---|---|---|
| checkpoint-3000/model.safetensors | Weights | 249.6 MB | 433f68b785fb |
| checkpoint-3000/rng_state.pth | Weights | 14.7 KB | c435b02562d2 |
| checkpoint-3000/training_args.bin | Weights | 6.4 KB | a41e504646b4 |
| checkpoint-6000/model.safetensors | Weights | 249.6 MB | 6ec1cff689b8 |
| checkpoint-6000/rng_state.pth | Weights | 14.7 KB | fba986e6d9da |
| checkpoint-6000/training_args.bin | Weights | 6.4 KB | a41e504646b4 |
| checkpoint-9000/model.safetensors | Weights | 249.6 MB | a43c6e4bd4a1 |
| checkpoint-9000/rng_state.pth | Weights | 14.7 KB | e638a564e12f |
| checkpoint-9000/training_args.bin | Weights | 6.4 KB | a41e504646b4 |
| model.safetensors | Weights | 249.6 MB | a43c6e4bd4a1 |
| training_args.bin | Weights | 6.4 KB | a41e504646b4 |
| added_tokens.json | Configuration | 27.7 KB | — |
| checkpoint-3000/added_tokens.json | Configuration | 27.7 KB | — |
| checkpoint-3000/config.json | Configuration | 803 B | — |
| checkpoint-3000/generation_config.json | Configuration | 172 B | — |
| checkpoint-3000/special_tokens_map.json | Configuration | 22.6 KB | — |
| checkpoint-3000/trainer_state.json | Configuration | 168.3 KB | — |
| checkpoint-6000/added_tokens.json | Configuration | 27.7 KB | — |
| checkpoint-6000/config.json | Configuration | 803 B | — |
| checkpoint-6000/generation_config.json | Configuration | 172 B | — |
| checkpoint-6000/special_tokens_map.json | Configuration | 22.6 KB | — |
| checkpoint-6000/trainer_state.json | Configuration | 337.6 KB | — |
| checkpoint-9000/added_tokens.json | Configuration | 27.7 KB | — |
| checkpoint-9000/config.json | Configuration | 803 B | — |
| checkpoint-9000/generation_config.json | Configuration | 172 B | — |
| checkpoint-9000/special_tokens_map.json | Configuration | 22.6 KB | — |
| checkpoint-9000/trainer_state.json | Configuration | 506.8 KB | — |
| config.json | Configuration | 803 B | — |
| special_tokens_map.json | Configuration | 22.6 KB | — |
| README.md | Documentation | 2.0 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
| checkpoint-3000/spiece.model | Tokenizer | 1.2 MB | 8d4c190acbc7 |
| checkpoint-3000/tokenizer_config.json | Tokenizer | 233.6 KB | — |
| checkpoint-6000/spiece.model | Tokenizer | 1.2 MB | 8d4c190acbc7 |
| checkpoint-6000/tokenizer_config.json | Tokenizer | 233.6 KB | — |
| checkpoint-9000/spiece.model | Tokenizer | 1.2 MB | 8d4c190acbc7 |
| checkpoint-9000/tokenizer_config.json | Tokenizer | 233.6 KB | — |
| spiece.model | Tokenizer | 1.2 MB | 8d4c190acbc7 |
| tokenizer_config.json | Tokenizer | 233.6 KB | — |
Released by Francesca Padovani through its official repository on Hugging Face.
| Precision | Weights in memory |
|---|---|
| As published | 998.3 MB |
| 16-bit | 0.2 GB |
| 8-bit | 0.1 GB |
| 4-bit | 0.1 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
About 0.3 GB at 16-bit and 0.1 GB at 4-bit: the weights (125M parameters) plus a working margin. A long context needs more.
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Model · Text generation
This model is a fine-tuned version of francesca9805/ppt-wc-uniform-newlex-nor-before-100mb-packed-bfdisoseed3407. It has been trained using TRL. This model was trained with SFT.
Model · Text generation
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Model · Text generation
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This model is a fine-tuned version of fpadovani/arb-arab-100mb-ppt-shuff-dyck-100mbseed10. It has been trained using TRL. This model was trained with SFT.
This model is a fine-tuned version of fpadovani/arb-arab-100mb-ppt-Dp-100mbseed10. It has been trained using TRL. This model was trained with SFT.
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