vbatts/llama.cpp
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Fix variable

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Galunid 2023-10-31 03:52:52 +01:00
parent b9c664ab2f
commit 0743f7a900
1 changed files with 3 additions and 5 deletions
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8
model.py
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@ -693,10 +693,10 @@ class RefactModel(Model):
n_head = self.hparams["n_head"] n_head = self.hparams["n_head"]
n_head_kv = 1 n_head_kv = 1
head_dim = self.hparams["n_embd"] // n_head head_dim = self.hparams["n_embd"] // n_head
block_count = self.hparams["n_layer"]
tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count)
block_count = self.hparams["n_layer"]
tensors = dict(self.get_tensors()) tensors = dict(self.get_tensors())
for i in range(block_count): for i in range(block_count):
if f"transformer.h.{i}.attn.kv.weight" in tensors: if f"transformer.h.{i}.attn.kv.weight" in tensors:
@ -755,14 +755,12 @@ class RefactModel(Model):
class PersimmonModel(Model): class PersimmonModel(Model):
def set_gguf_parameters(self): def set_gguf_parameters(self):
block_count = self.hparams["num_layers"] block_count = self.hparams.get("num_layers", self.hparams.get("num_hidden_layers"))
head_count = self.hparams["num_attention_heads"] head_count = self.hparams["num_attention_heads"]
head_count_kv = head_count head_count_kv = head_count
ctx_length = self.hparams["seq_length"]
hidden_size = self.hparams["hidden_size"] hidden_size = self.hparams["hidden_size"]
self.gguf_writer.add_name('persimmon-8b-chat') self.gguf_writer.add_name('persimmon-8b-chat')
self.gguf_writer.add_context_length(ctx_length)
self.gguf_writer.add_embedding_length(hidden_size) self.gguf_writer.add_embedding_length(hidden_size)
self.gguf_writer.add_block_count(block_count) self.gguf_writer.add_block_count(block_count)
self.gguf_writer.add_feed_forward_length(self.hparams["ffn_hidden_size"]) self.gguf_writer.add_feed_forward_length(self.hparams["ffn_hidden_size"])
@ -782,7 +780,7 @@ class PersimmonModel(Model):
# self.gguf_writer.add_eos_token_id(71013) # self.gguf_writer.add_eos_token_id(71013)
def write_tensors(self): def write_tensors(self):
block_count = self.hparams["num_layers"] 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) tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count)
print(tensor_map) print(tensor_map)
for name, data in self.get_tensors(): for name, data in self.get_tensors():