120 lines
4.0 KiB
Python
120 lines
4.0 KiB
Python
from typing import Optional
|
|
import os
|
|
import json
|
|
from dataclasses import dataclass
|
|
|
|
from huggingface_hub import hf_hub_download
|
|
|
|
from text_generation_server.utils.weights import DefaultWeightsLoader, WeightsLoader
|
|
|
|
|
|
@dataclass
|
|
class _QuantizerConfig:
|
|
bits: int
|
|
checkpoint_format: Optional[str]
|
|
desc_act: bool
|
|
groupsize: int
|
|
quant_method: str
|
|
sym: bool
|
|
|
|
|
|
# We should probably do this with Pytantic JSON deserialization,
|
|
# but for now we'll stay close to the old _set_gptq_params.
|
|
def _get_quantizer_config(model_id, revision):
|
|
bits = 4
|
|
groupsize = -1
|
|
quant_method = "gptq"
|
|
checkpoint_format = None
|
|
sym = True
|
|
desc_act = False
|
|
|
|
filename = "config.json"
|
|
try:
|
|
if os.path.exists(os.path.join(model_id, filename)):
|
|
filename = os.path.join(model_id, filename)
|
|
else:
|
|
filename = hf_hub_download(model_id, filename=filename, revision=revision)
|
|
with open(filename, "r") as f:
|
|
data = json.load(f)
|
|
bits = data["quantization_config"]["bits"]
|
|
groupsize = data["quantization_config"]["group_size"]
|
|
# Order is important here, desc_act is missing on some real models
|
|
quant_method = data["quantization_config"]["quant_method"]
|
|
checkpoint_format = data["quantization_config"].get("checkpoint_format")
|
|
sym = data["quantization_config"]["sym"]
|
|
desc_act = data["quantization_config"]["desc_act"]
|
|
except Exception:
|
|
filename = "quantize_config.json"
|
|
try:
|
|
if os.path.exists(os.path.join(model_id, filename)):
|
|
filename = os.path.join(model_id, filename)
|
|
else:
|
|
filename = hf_hub_download(
|
|
model_id, filename=filename, revision=revision
|
|
)
|
|
with open(filename, "r") as f:
|
|
data = json.load(f)
|
|
bits = data["bits"]
|
|
groupsize = data["group_size"]
|
|
sym = data["sym"]
|
|
desc_act = data["desc_act"]
|
|
if "version" in data and data["version"] == "GEMM":
|
|
quant_method = "awq"
|
|
except Exception:
|
|
filename = "quant_config.json"
|
|
try:
|
|
if os.path.exists(os.path.join(model_id, filename)):
|
|
filename = os.path.join(model_id, filename)
|
|
else:
|
|
filename = hf_hub_download(
|
|
model_id, filename=filename, revision=revision
|
|
)
|
|
with open(filename, "r") as f:
|
|
data = json.load(f)
|
|
bits = data["w_bit"]
|
|
groupsize = data["q_group_size"]
|
|
desc_act = data["desc_act"]
|
|
if "version" in data and data["version"] == "GEMM":
|
|
quant_method = "awq"
|
|
except Exception:
|
|
pass
|
|
|
|
return _QuantizerConfig(
|
|
bits=bits,
|
|
groupsize=groupsize,
|
|
quant_method=quant_method,
|
|
checkpoint_format=checkpoint_format,
|
|
sym=sym,
|
|
desc_act=desc_act,
|
|
)
|
|
|
|
|
|
def get_loader(
|
|
quantize: Optional[str], model_id: str, revision: Optional[str]
|
|
) -> WeightsLoader:
|
|
quantizer_config = _get_quantizer_config(model_id, revision)
|
|
if quantize in {"awq", "gptq"}:
|
|
from text_generation_server.layers.gptq import GPTQWeightsLoader
|
|
|
|
return GPTQWeightsLoader(
|
|
bits=quantizer_config.bits,
|
|
desc_act=quantizer_config.desc_act,
|
|
groupsize=quantizer_config.groupsize,
|
|
quant_method=quantizer_config.quant_method,
|
|
quantize=quantize,
|
|
sym=quantizer_config.sym,
|
|
)
|
|
elif quantize == "exl2":
|
|
from text_generation_server.layers.exl2 import Exl2WeightsLoader
|
|
|
|
return Exl2WeightsLoader()
|
|
elif quantize == "marlin":
|
|
from text_generation_server.layers.marlin import MarlinWeightsLoader
|
|
|
|
return MarlinWeightsLoader(
|
|
bits=quantizer_config.bits,
|
|
is_marlin_24=quantizer_config.checkpoint_format == "marlin_24",
|
|
)
|
|
else:
|
|
return DefaultWeightsLoader()
|