convert-hf : save memory with lazy evaluation (#7075)

* convert-hf : begin refactoring write_tensor

* convert : upgrade to sentencepiece v0.2.0

* convert-hf : remove unused n_dims in extra_*_tensors

* convert-hf : simplify MoE weights stacking

* convert-hf : flake8 linter doesn't like semicolons

* convert-hf : allow unusual model part names

For example, loading `model-00001-of-00001.safetensors` now works.

* convert-hf : fix stacking MoE expert tensors

`torch.stack` and `torch.cat` don't do the same thing.

* convert-hf : fix Mamba conversion

Tested to work even with a SentencePiece-based tokenizer.

* convert : use a string for the SentencePiece tokenizer path

* convert-hf : display tensor shape

* convert-hf : convert norms to f32 by default

* convert-hf : sort model part names

`os.listdir` is said to list files in arbitrary order.
Sorting the file names should let "model-00009-of-00042.safetensors"
be loaded before "model-00010-of-00042.safetensors".

* convert-hf : use an ABC for Model again

It seems Protocol can't be used as a statically type-checked ABC,
because its subclasses also can't be instantiated. (why did it seem to work?)

At least there's still a way to throw an error when forgetting to define
the `model_arch` property of any registered Model subclasses.

* convert-hf : use a plain class for Model, and forbid direct instantiation

There are no abstract methods used anyway,
so using ABC isn't really necessary.

* convert-hf : more consistent formatting of cmdline args

* convert-hf : align the message logged for converted tensors

* convert-hf : fix Refact conversion

* convert-hf : save memory with lazy evaluation

* convert-hf : flake8 doesn't like lowercase L as a variable name

* convert-hf : remove einops requirement for InternLM2

* convert-hf : faster model parts loading

Instead of pre-loading them all into a dict, iterate on the tensors
in the model parts progressively as needed in Model.write_tensors

Conversion for some architectures relies on checking for the presence
of specific tensor names, so for multi-part models, the weight map is read
from the relevant json file to quickly get these names up-front.

* convert-hf : minor changes for consistency

* gguf-py : add tqdm as a dependency

It's small, and used for a progress bar
in GGUFWriter.write_tensors_to_file

gguf-py/gguf/vocab.py

@@ -4,7 +4,7 @@ import logging
 import json
 import os
 from pathlib import Path
-from typing import Any, Callable
+from typing import Any, Callable, Sequence, Mapping, Iterable
 
 from .gguf_writer import GGUFWriter
 
@@ -15,11 +15,11 @@ class SpecialVocab:
     merges: list[str]
     add_special_token: dict[str, bool]
     special_token_ids: dict[str, int]
-    chat_template: str | None
+    chat_template: str | Sequence[Mapping[str, str]] | None
 
     def __init__(
         self, path: str | os.PathLike[str], load_merges: bool = False,
-        special_token_types: tuple[str, ...] | None = None,
+        special_token_types: Iterable[str] | None = None,
         n_vocab: int | None = None,
     ):
         self.special_token_ids = {}