vbatts/llama.cpp
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

convert : fix tensors using grad in some models

Browse source
This commit is contained in:
Galunid 2023-11-22 21:31:30 +01:00
parent 8e672efe63
commit 436253f5a4
1 changed files with 8 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

8
convert-hf-to-gguf.py
View file

@ -51,6 +51,7 @@ class Model:
def set_vocab(self):
self._set_vocab_gpt2()
@torch.no_grad()
def get_tensors(self) -> Iterator[tuple[str, Tensor]]:
for part_name in self.part_names:
print(f"gguf: loading model part '{part_name}'")
@ -81,6 +82,7 @@ class Model:
self.gguf_writer.add_head_count(n_head)
self.gguf_writer.add_parallel_residual(self.hparams.get("use_parallel_residual", True))
@torch.no_grad()
def write_tensors(self):
block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer")))
tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count)
@ -327,6 +329,7 @@ class BloomModel(Model):
self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"])
self.gguf_writer.add_file_type(self.ftype)
@torch.no_grad()
def write_tensors(self):
block_count = self.hparams["n_layer"]
tensors = dict(self.get_tensors())
@ -421,6 +424,7 @@ class MPTModel(Model):
self.gguf_writer.add_clamp_kqv(self.hparams["attn_config"]["clip_qkv"])
self.gguf_writer.add_max_alibi_bias(self.hparams["attn_config"]["alibi_bias_max"])
@torch.no_grad()
def write_tensors(self):
block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers"))
tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count)
@ -506,6 +510,7 @@ class BaichuanModel(Model):
self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
@torch.no_grad()
def write_tensors(self):
# Collect tensors from generator object
model_kv = dict(self.get_tensors())
@ -608,6 +613,7 @@ class FalconModel(Model):
self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"])
self.gguf_writer.add_file_type(self.ftype)
@torch.no_grad()
def write_tensors(self):
block_count = self.hparams.get("num_hidden_layers")
if block_count is None:
@ -713,6 +719,7 @@ class RefactModel(Model):
self.gguf_writer.add_layer_norm_rms_eps(self.hparams["layer_norm_epsilon"])
self.gguf_writer.add_file_type(self.ftype)
@torch.no_grad()
def write_tensors(self):
hidden_dim = self.hparams["n_embd"]
inner_dim = 4 * hidden_dim
@ -798,6 +805,7 @@ class PersimmonModel(Model):
# self.gguf_writer.add_bos_token_id(71013)
# self.gguf_writer.add_eos_token_id(71013)
@torch.no_grad()
def write_tensors(self):
block_count = self.hparams.get("num_layers", self.hparams.get("num_hidden_layers"))
tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count)