vbatts/llama.cpp
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Remove is_lora in convert_hf_to_gguf, which is removed in master.

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Qingtao Li 2024-10-11 14:41:31 +08:00
parent 94502e44a7
commit f673699460
1 changed files with 1 additions and 3 deletions
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4
convert_hf_to_gguf.py
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@ -65,7 +65,6 @@ class Model:
model_name: str | None model_name: str | None
metadata_override: Path | None metadata_override: Path | None
dir_model_card: Path dir_model_card: Path
is_lora: bool
enable_t_mac: bool enable_t_mac: bool
kcfg_file: Path | None kcfg_file: Path | None
@ -76,7 +75,7 @@ class Model:
use_temp_file: bool = False, eager: bool = False, use_temp_file: bool = False, eager: bool = False,
metadata_override: Path | None = None, model_name: str | None = None, metadata_override: Path | None = None, model_name: str | None = None,
split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False, split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False,
small_first_shard: bool = False, hparams: dict[str, Any] | None = None, is_lora: bool = False, small_first_shard: bool = False, hparams: dict[str, Any] | None = None,
enable_t_mac: bool = False, kcfg_file: Path | None = None): enable_t_mac: bool = False, kcfg_file: Path | None = None):
if type(self) is Model: if type(self) is Model:
raise TypeError(f"{type(self).__name__!r} should not be directly instantiated") raise TypeError(f"{type(self).__name__!r} should not be directly instantiated")
@ -99,7 +98,6 @@ class Model:
self.metadata_override = metadata_override self.metadata_override = metadata_override
self.model_name = model_name self.model_name = model_name
self.dir_model_card = dir_model # overridden in convert_lora_to_gguf.py self.dir_model_card = dir_model # overridden in convert_lora_to_gguf.py
self.is_lora = is_lora # true if model is used inside convert_lora_to_gguf.py
self.enable_t_mac = enable_t_mac self.enable_t_mac = enable_t_mac
self.kcfg_file = kcfg_file self.kcfg_file = kcfg_file
# Apply heuristics to figure out typical tensor encoding based on first layer tensor encoding type # Apply heuristics to figure out typical tensor encoding based on first layer tensor encoding type