| from __future__ import annotations |
|
|
| from typing import Literal |
|
|
|
|
| def fill_templated_filename(filename: str, output_type: str | None) -> str: |
| |
| ftype_lowercase: str = output_type.lower() if output_type is not None else "" |
| ftype_uppercase: str = output_type.upper() if output_type is not None else "" |
| return filename.format(ftype_lowercase, |
| outtype=ftype_lowercase, ftype=ftype_lowercase, |
| OUTTYPE=ftype_uppercase, FTYPE=ftype_uppercase) |
|
|
|
|
| def model_weight_count_rounded_notation(model_params_count: int, min_digits: int = 2) -> str: |
| if model_params_count > 1e12 : |
| |
| scaled_model_params = model_params_count * 1e-12 |
| scale_suffix = "T" |
| elif model_params_count > 1e9 : |
| |
| scaled_model_params = model_params_count * 1e-9 |
| scale_suffix = "B" |
| elif model_params_count > 1e6 : |
| |
| scaled_model_params = model_params_count * 1e-6 |
| scale_suffix = "M" |
| else: |
| |
| scaled_model_params = model_params_count * 1e-3 |
| scale_suffix = "K" |
|
|
| fix = max(min_digits - len(str(round(scaled_model_params)).lstrip('0')), 0) |
|
|
| return f"{scaled_model_params:.{fix}f}{scale_suffix}" |
|
|
|
|
| def size_label(total_params: int, shared_params: int, expert_params: int, expert_count: int) -> str: |
|
|
| if expert_count > 0: |
| pretty_size = model_weight_count_rounded_notation(abs(shared_params) + abs(expert_params), min_digits=2) |
| size_class = f"{expert_count}x{pretty_size}" |
| else: |
| size_class = model_weight_count_rounded_notation(abs(total_params), min_digits=2) |
|
|
| return size_class |
|
|
|
|
| def naming_convention(model_name: str | None, base_name: str | None, finetune_string: str | None, version_string: str | None, size_label: str | None, output_type: str | None, model_type: Literal['vocab', 'LoRA'] | None = None) -> str: |
| |
|
|
| if base_name is not None: |
| name = base_name.strip().replace(' ', '-').replace('/', '-') |
| elif model_name is not None: |
| name = model_name.strip().replace(' ', '-').replace('/', '-') |
| else: |
| name = "ggml-model" |
|
|
| parameters = f"-{size_label}" if size_label is not None else "" |
|
|
| finetune = f"-{finetune_string.strip().replace(' ', '-')}" if finetune_string is not None else "" |
|
|
| version = f"-{version_string.strip().replace(' ', '-')}" if version_string is not None else "" |
|
|
| encoding = f"-{output_type.strip().replace(' ', '-').upper()}" if output_type is not None else "" |
|
|
| kind = f"-{model_type.strip().replace(' ', '-')}" if model_type is not None else "" |
|
|
| return f"{name}{parameters}{finetune}{version}{encoding}{kind}" |
|
|