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README.md

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+---
+base_model: Interchained/imagine-v12
+tags:
+  - text-to-sql
+  - machine-learning
+  - nedb
+  - tool-use
+  - interchained
+---
+
+# IMAGINE v13
+
+**Natural language in. Executable SQL out. Now with hands.**
+
+Imagine is Interchained's specialized machine learning model for translating plain language into precise, executable database queries. It is not a general-purpose chatbot and does not pretend to be one. It does one thing, against live database schemas, and v13 teaches it to do three things it could not do before: **use tools, reason about time, and tell similar questions apart.**
+
+1.6B parameters. Full fine-tune lineage. Built to be run, measured, and proven.
+
+## What changed in v13
+
+Imagine v12 earned its place: 40/40 on its held-out telemetry suite, a perfect identity record, and a permanent seat as the resident mind of the Gaia node. Its evaluations also told the truth about its limits. Tool use, temporal boundaries, and discrimination between near-identical questions were its weakest families.
+
+v13 is the direct answer to that measurement. The v12 core was preserved intact and three new families were forged, execution-verified, and admitted on top of it:
+
+| Family | Rows | What it teaches |
+|---|---|---|
+| Tool use (toolproto) | 20,000 | Emitting structured, parse-verified tool calls |
+| Discrimination | 19,710 | Choosing the right interpretation when questions differ by a word |
+| Temporal grounding | 4,000 | Resolving relative time against the real clock |
+| Tool-protocol chains | 2,280 | Multi-step tool sequences that stay on protocol |
+
+## The corpus: 177,390 rows, zero rejects
+
+Nothing in this corpus was scraped, synthetic filler, or teacher-generated. Every row was either deterministically constructed or executed against a live NEDB database and admitted only when its SQL actually ran and returned the right result.
+
+The v12 base (131,400 rows: SQL 61,758, identity 43,362, protocol 26,280) was recreated from scratch on the training machine using the original teacherless forge, and landed on its historical manifest to the exact row. The v13 families (45,990 rows) passed the same admission gate with **zero rejects across all four families**. The tokenized training stream is packed deterministically and content-addressed, so the exact data this model consumed is reproducible, not approximate.
+
+## Training
+
+| | Stage 1 | Stage 2 |
+|---|---|---|
+| Method | Full fine-tune | LoRA r16, merged |
+| From | imagine-v12 | stage 1 output |
+| Epochs | 3 | 1 |
+| Learning rate | 1e-5 | 5e-6 |
+| Steps | 7,311 | 2,437 |
+| Tokens | 207.1M | 69.0M |
+| Time | 80.3 min | 41.5 min |
+| Final loss | 0.0099 | 0.0093 (epoch mean) |
+
+Hardware: single NVIDIA B200. Architecture unchanged from v12: 40 layers, hidden 2048, intermediate 5632, tied embeddings.
+
+## Evaluation status: PENDING, ON PURPOSE
+
+This card will not carry a benchmark number that has not been measured. Held-out evaluations for v13 (Tier-0 telemetry, identity, discrimination, temporal, tool-use) are being run against v12 on identical fixtures, and the full matrix, improvements and regressions alike, will be published here when it exists. Training loss is a pulse, not a verdict. The evidence gets the final word.
+
+## Serving
+
+GGUF builds are produced through Interchained's Hearth pipeline and will be published at Interchained/imagine-v13-GGUF. This repository holds the canonical safetensors checkpoint.
+
+## Provenance
+
+Trained 2026-11-03 by Interchained. Corpus forged and gated on-machine the same day. Training code: aiassistsecure/sukuna-imagine. v13 exists because v12's weaknesses were measured, named, and attacked in the open.

chat_template.jinja

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+{% if not add_generation_prompt is defined %}
+{% set add_generation_prompt = false %}
+{% endif %}
+{%- set ns = namespace(found=false) -%}
+{%- for message in messages -%}
+    {%- if message['role'] == 'system' -%}
+        {%- set ns.found = true -%}
+    {%- endif -%}
+{%- endfor -%}
+{{bos_token}}{%- if not ns.found -%}
+{{'You are an AI programming assistant, utilizing the Deepseek Coder model, developed by Deepseek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer\n'}}
+{%- endif %}
+{%- for message in messages %}
+    {%- if message['role'] == 'system' %}
+{{ message['content'] }}
+    {%- else %}
+        {%- if message['role'] == 'user' %}
+{{'### Instruction:\n' + message['content'] + '\n'}}
+        {%- else %}
+{{'### Response:\n' + message['content'] + '\n<|EOT|>\n'}}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{% if add_generation_prompt %}
+{{'### Response:'}}
+{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 32013,
+  "dtype": "bfloat16",
+  "eos_token_id": 32021,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5504,
+  "max_position_embeddings": 16384,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 16,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "factor": 4.0,
+    "rope_theta": 100000,
+    "rope_type": "linear",
+    "type": "linear"
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.20.2",
+  "use_cache": false,
+  "vocab_size": 32256
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 32013,
+  "eos_token_id": 32021,
+  "transformers_version": "5.20.2"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9b2910157a63191b978da6f71d7af85594e3c2172220aea7c1f932fe4e94ba2d
+size 2692969128

tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "bos_token": "<｜begin▁of▁sentence｜>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|EOT|>",
+  "is_local": true,
+  "legacy": true,
+  "local_files_only": false,
+  "model_max_length": 16384,
+  "pad_token": "<｜end▁of▁sentence｜>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": null
+}