/**
 * export/hf.ts — the Hugging Face repository sidecar files.
 *
 * The JSON/markdown that turns raw weights into an ingestible HF model repo:
 *   • config.json            — architecture config (model_type "evermind")
 *   • generation_config.json — default decoding params
 *   • tokenizer.json         — the byte-level BPE in HF `tokenizers` format
 *   • README.md              — the model card (YAML front-matter + body)
 *
 * The tokenizer uses the same GPT-2 byte→unicode alphabet as {@link BPETokenizer}
 * (a ByteLevel pre-tokenizer/decoder), so HF `tokenizers` / transformers.js
 * reproduce our encode/decode.
 */
import type { EvermindLM } from "../lm/evermind_lm.js";
import type { BPETokenizer } from "../tokenizer/bpe.js";
export interface HfMeta {
    name?: string;
    version?: string;
    license?: string;
    author?: string;
    description?: string;
    tags?: string[];
}
/** HF `config.json` describing the Evermind architecture. */
export declare function configJson(lm: EvermindLM): Record<string, unknown>;
/** HF `generation_config.json` — greedy by default, matching the reference. */
export declare function generationConfigJson(): Record<string, unknown>;
/** HF `tokenizer.json` (the `tokenizers` fast-tokenizer format) for the BPE. */
export declare function tokenizerJson(tok: BPETokenizer): Record<string, unknown>;
/** HF model card (`README.md`) with YAML front-matter. */
export declare function modelCardMarkdown(lm: EvermindLM, meta?: HfMeta): string;
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