py : re-enable mmap in convert hf (#4732)

* update: awq support llama-7b model

* update: change order

* update: benchmark results for llama2-7b

* update: mistral 7b v1 benchmark

* update: support 4 models

* fix: Readme

* update: ready for PR

* update: readme

* fix: readme

* update: change order import

* black

* format code

* update: work for bot mpt and awqmpt

* update: readme

* Rename to llm_build_ffn_mpt_awq

* Formatted other files

* Fixed params count

* fix: remove code

* update: more detail for mpt

* fix: readme

* fix: readme

* update: change folder architecture

* fix: common.cpp

* fix: readme

* fix: remove ggml_repeat

* update: cicd

* update: cicd

* uppdate: remove use_awq arg

* update: readme

* llama : adapt plamo to new ffn

ggml-ci

* fix: update torch version

---------

Co-authored-by: Trần Đức Nam <[email protected]>
Co-authored-by: Le Hoang Anh <[email protected]>
Co-authored-by: Georgi Gerganov <[email protected]>

Author: 4 people

awq-py/requirements.txt

@@ -1,2 +1,2 @@
-torch>=2.0.0
+torch>=2.1.1
 transformers>=4.32.0

convert-hf-to-gguf.py

@@ -59,7 +59,7 @@ def get_tensors(self) -> Iterator[tuple[str, Tensor]]:
                 from safetensors import safe_open
                 ctx = cast(ContextManager[Any], safe_open(self.dir_model / part_name, framework="pt", device="cpu"))
             else:
-                ctx = contextlib.nullcontext(torch.load(str(self.dir_model / part_name), map_location="cpu", weights_only=True))
+                ctx = contextlib.nullcontext(torch.load(str(self.dir_model / part_name), map_location="cpu", mmap=True, weights_only=True))
 
             with ctx as model_part:
                 for name in model_part.keys():