Add root config.json to enable Hub download tracking; document it in README
Browse files- README.md +1 -0
- config.json +15 -0
README.md
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@@ -41,6 +41,7 @@ time-series encoder onto a pretrained LLM.
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| `stage-2/` | **Stage 2** | Stage 1 + a short alignment stage that interleaves the two modalities (best multimodal results); context extended to 4096. `model.safetensors` + `config.json` |
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| `tokenizer/` | — | 131k-vocabulary BPE tokenizer (trained from scratch) |
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| `model.py` · `tokenizer.py` | — | Minimal inference implementation (`Chronicle`, `ChronicleConfig`, `ChronicleTokenizer`) |
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## Architecture
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| `stage-2/` | **Stage 2** | Stage 1 + a short alignment stage that interleaves the two modalities (best multimodal results); context extended to 4096. `model.safetensors` + `config.json` |
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| `tokenizer/` | — | 131k-vocabulary BPE tokenizer (trained from scratch) |
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| `model.py` · `tokenizer.py` | — | Minimal inference implementation (`Chronicle`, `ChronicleConfig`, `ChronicleTokenizer`) |
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| `config.json` | — | Repo-level model metadata (mirrors the stage-2 architecture); the per-stage `config.json` files remain authoritative for loading |
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## Architecture
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config.json
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{
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"model_type": "chronicle",
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"architectures": ["Chronicle"],
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"checkpoints": ["stage-1", "stage-2"],
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"default_checkpoint": "stage-2",
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"sequence_len": 4096,
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"vocab_size": 131072,
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"n_layer": 16,
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"n_head": 8,
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"n_kv_head": 4,
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"n_embd": 1024,
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"patch_len": 32,
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"num_quantiles": 21,
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"torch_dtype": "bfloat16"
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}
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