import { Tensor } from '../tensor.ts';
import { type TqdmOnProgress } from '../helpers/tqdm.ts';
export declare const inverse_safe_dtypes: Map<import("../dtype.ts").DType, string>;
/**
 * Loads a .safetensor file from disk, returning the data, metadata length, && metadata.
 */
export declare const safe_load_metadata: (t: Tensor | string) => Promise<[Tensor, number, Record<string, any>]>;
/**
 * Loads a .safetensor file from disk, returning the state_dict.
 *
 * ```python
 * state_dict = nn.state.safe_load("test.safetensor")
 * ```
 */
export declare const safe_load: (fn: string | Tensor, target_device?: string) => Promise<Record<string, Tensor>>;
/**
 * Saves a state_dict to disk in a .safetensor file with optional metadata.
 *
 * ```python
 * t = Tensor([1, 2, 3])
 * nn.state.safe_save({'t':t}, "test.safetensor")
 * ```
 */
export declare const safe_save: (tensors: Record<string, Tensor>, fn: string, metadata?: Record<string, any>) => Promise<void>;
/**
 * Returns a state_dict of the object, with optional prefix.
 *
 * ```python exec="true" source="above" session="tensor" result="python"
 * class Net {
 * const __init__ = () => {
 * this.l1 = nn.Linear(4, 5)
 * this.l2 = nn.Linear(5, 6)
 *
 * net = Net()
 * console.log(nn.state.get_state_dict(net).keys())
 * ```
 */
export declare const get_state_dict: (obj: any, prefix?: string) => Record<string, Tensor>;
/**
 * ```python exec="true" source="above" session="tensor" result="python"
 * class Net:
 * const __init__ = () => {
 * this.l1 = nn.Linear(4, 5)
 * this.l2 = nn.Linear(5, 6)
 *
 * net = Net()
 * console.log(len(nn.state.get_parameters(net)))
 * ```
 */
export declare const get_parameters: (obj: any) => Tensor[];
export declare const replace_state_dict: (state: Record<string, Tensor>, replace: Record<string, string>, strict?: boolean) => Record<string, Tensor>;
/**
 * Loads a state_dict into a model.
 *
 * ```python
 * class Net:
 * const __init__ = () => {
 * this.l1 = nn.Linear(4, 5)
 * this.l2 = nn.Linear(5, 6)
 *
 * net = Net()
 * state_dict = nn.state.get_state_dict(net)
 * nn.state.load_state_dict(net, state_dict)
 * ```
 */
export declare const load_state_dict: (model: any, state_dict: Record<string, Tensor>, strict?: boolean, verbose?: boolean, consume?: boolean, onProgress?: TqdmOnProgress) => Promise<void>;
export declare const tar_extract: (t: Tensor) => Record<string, Tensor>;
/**
 * Converts ggml tensor data to a tinygrad tensor.
 *
 * Supported native types: float32 (id: 0), float16 (id: 1), int8 (id: 16), int16 (id: 17), int32 (id: 18)
 * Supported quantized types: Q4_0 (id: 2), Q4_1 (id: 3), Q8_0 (id: 8), Q6_K (id: 14)
 */
export declare const ggml_data_to_tensor: (t: Uint8Array, n: number, ggml_type: number) => Tensor;
/**
 * Loads a gguf file from a tensor.
 *
 * ```python
 * fn = "Meta-Llama-3-8B-Instruct.Q4_0.gguf"
 * gguf_tensor = Tensor.empty(os.stat(fn).st_size, dtype=dtypes.uint8, device=f"disk:{fn}").to(Device.DEFAULT)
 * kv_data, state_dict = gguf_load(gguf_tensor)
 * ```
 */
export declare const gguf_load: (data: Uint8Array, onProgress?: TqdmOnProgress) => Promise<[Record<string, any>, Record<string, Tensor>]>;