From 173788db0fc956b594323c983cfca1fee47b25a2 Mon Sep 17 00:00:00 2001 From: stefan Date: Mon, 10 Jun 2024 17:51:10 +0000 Subject: [PATCH] update: convert-hf-to-gguf.py cleanup for Qwen2MoeForCausalLM --- convert-hf-to-gguf.py | 44 ++----------------------------------------- 1 file changed, 2 insertions(+), 42 deletions(-) diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 4216493fd44eb1..23b28853f85f45 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -1624,52 +1624,12 @@ class Qwen2MoeModel(Model): model_arch = gguf.MODEL_ARCH.QWEN2MOE def set_gguf_parameters(self): - self.gguf_writer.add_name(self.dir_model.name) - self.gguf_writer.add_block_count(self.block_count) - - if (n_ctx := self.find_hparam(["max_position_embeddings", "n_ctx"], optional=True)) is not None: - self.gguf_writer.add_context_length(n_ctx) - logger.info(f"gguf: context length = {n_ctx}") - - n_embd = self.find_hparam(["hidden_size", "n_embd"]) - self.gguf_writer.add_embedding_length(n_embd) - logger.info(f"gguf: embedding length = {n_embd}") - - n_head = self.find_hparam(["num_attention_heads", "n_head"]) - self.gguf_writer.add_head_count(n_head) - logger.info(f"gguf: head count = {n_head}") - - if (n_head_kv := self.hparams.get("num_key_value_heads")) is not None: - self.gguf_writer.add_head_count_kv(n_head_kv) - logger.info(f"gguf: key-value head count = {n_head_kv}") - - if (rope_theta := self.hparams.get("rope_theta")) is not None: - self.gguf_writer.add_rope_freq_base(rope_theta) - logger.info(f"gguf: rope theta = {rope_theta}") - if (f_rms_eps := self.hparams.get("rms_norm_eps")) is not None: - self.gguf_writer.add_layer_norm_rms_eps(f_rms_eps) - logger.info(f"gguf: rms norm epsilon = {f_rms_eps}") - if (f_norm_eps := self.find_hparam(["layer_norm_eps", "layer_norm_epsilon", "norm_epsilon"], optional=True)) is not None: - self.gguf_writer.add_layer_norm_eps(f_norm_eps) - logger.info(f"gguf: layer norm epsilon = {f_norm_eps}") - - if (n_experts_used := self.hparams.get("num_experts_per_tok")) is not None: - self.gguf_writer.add_expert_used_count(n_experts_used) - logger.info(f"gguf: experts used count = {n_experts_used}") - - if (n_experts := self.find_hparam(["num_experts", "num_local_experts"])) is not None: + super().set_gguf_parameters() + if (n_experts := self.hparams.get("num_experts")) is not None: self.gguf_writer.add_expert_count(n_experts) - if (moe_intermediate_size := self.hparams.get("moe_intermediate_size")) is not None: self.gguf_writer.add_expert_feed_forward_length(moe_intermediate_size) logger.info(f"gguf: expert feed forward length = {moe_intermediate_size}") - - if (shared_expert_intermediate_size := self.find_hparam(["shared_expert_intermediate_size","intermediate_size", "n_inner"])) is not None: - self.gguf_writer.add_feed_forward_length(shared_expert_intermediate_size) - logger.info(f"gguf: feed forward length = {shared_expert_intermediate_size}") - - self.gguf_writer.add_file_type(self.ftype) - logger.info(f"gguf: file type = {self.ftype}") _experts: list[dict[str, Tensor]] | None = None