Add QuIP# support (#4803)

It has to be installed manually for now.
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oobabooga 2023-12-06 00:01:01 -03:00 committed by GitHub
parent 6430acadde
commit 98361af4d5
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4 changed files with 95 additions and 8 deletions

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@ -143,6 +143,11 @@ loaders_and_params = OrderedDict({
'no_mmap',
'mlock'
],
'QuIP#': [
'trust_remote_code',
'no_use_fast',
'no_flash_attn',
]
})
loaders_samplers = {
@ -453,6 +458,43 @@ loaders_samplers = {
'skip_special_tokens',
'auto_max_new_tokens',
},
'QuIP#': {
'temperature',
'temperature_last',
'top_p',
'min_p',
'top_k',
'typical_p',
'epsilon_cutoff',
'eta_cutoff',
'tfs',
'top_a',
'repetition_penalty',
'presence_penalty',
'frequency_penalty',
'repetition_penalty_range',
'encoder_repetition_penalty',
'no_repeat_ngram_size',
'min_length',
'seed',
'do_sample',
'penalty_alpha',
'num_beams',
'length_penalty',
'early_stopping',
'mirostat_mode',
'mirostat_tau',
'mirostat_eta',
'grammar_file_row',
'grammar_string',
'guidance_scale',
'negative_prompt',
'ban_eos_token',
'custom_token_bans',
'add_bos_token',
'skip_special_tokens',
'auto_max_new_tokens',
},
}
loaders_model_types = {

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@ -1,4 +1,5 @@
import gc
import logging
import os
import re
import time
@ -23,6 +24,7 @@ import modules.shared as shared
from modules import RoPE, llama_attn_hijack, sampler_hijack
from modules.logging_colors import logger
from modules.models_settings import get_model_metadata
from modules.relative_imports import RelativeImport
transformers.logging.set_verbosity_error()
@ -69,6 +71,7 @@ def load_model(model_name, loader=None):
'ExLlamav2_HF': ExLlamav2_HF_loader,
'ctransformers': ctransformers_loader,
'AutoAWQ': AutoAWQ_loader,
'QuIP#': QuipSharp_loader,
}
metadata = get_model_metadata(model_name)
@ -321,6 +324,37 @@ def AutoAWQ_loader(model_name):
return model
def QuipSharp_loader(model_name):
try:
with RelativeImport("repositories/quip-sharp"):
from lib.utils.unsafe_import import model_from_hf_path
except:
logger.error(
"\nQuIP# has not been found. It must be installed manually for now.\n"
"For instructions on how to do that, please consult:\n"
"https://github.com/oobabooga/text-generation-webui/pull/4803\n"
)
return None, None
# This fixes duplicate logging messages after the import above.
handlers = logging.getLogger().handlers
if len(handlers) > 1:
logging.getLogger().removeHandler(handlers[1])
model_dir = Path(f'{shared.args.model_dir}/{model_name}')
if not all((model_dir / file).exists() for file in ['tokenizer_config.json', 'special_tokens_map.json', 'tokenizer.model']):
logger.error(f"Could not load the model because the tokenizer files could not be found in the model folder. Please download the following files from the original (unquantized) model into {model_dir}: special_tokens_map.json, tokenizer.json, tokenizer.model, tokenizer_config.json.")
return None, None
model, model_str = model_from_hf_path(
model_dir,
use_cuda_graph=False,
use_flash_attn=not shared.args.no_flash_attn
)
return model
def GPTQ_loader(model_name):
# Monkey patch

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@ -33,14 +33,24 @@ def get_model_metadata(model):
for k in settings[pat]:
model_settings[k] = settings[pat][k]
path = Path(f'{shared.args.model_dir}/{model}/config.json')
if path.exists():
hf_metadata = json.loads(open(path, 'r').read())
else:
hf_metadata = None
if 'loader' not in model_settings:
loader = infer_loader(model, model_settings)
if 'wbits' in model_settings and type(model_settings['wbits']) is int and model_settings['wbits'] > 0:
loader = 'AutoGPTQ'
if hf_metadata is not None and 'quip_params' in hf_metadata:
model_settings['loader'] = 'QuIP#'
else:
loader = infer_loader(model, model_settings)
if 'wbits' in model_settings and type(model_settings['wbits']) is int and model_settings['wbits'] > 0:
loader = 'AutoGPTQ'
model_settings['loader'] = loader
model_settings['loader'] = loader
# Read GGUF metadata
# GGUF metadata
if model_settings['loader'] in ['llama.cpp', 'llamacpp_HF', 'ctransformers']:
path = Path(f'{shared.args.model_dir}/{model}')
if path.is_file():
@ -57,9 +67,8 @@ def get_model_metadata(model):
model_settings['rope_freq_base'] = metadata['llama.rope.freq_base']
else:
# Read transformers metadata
path = Path(f'{shared.args.model_dir}/{model}/config.json')
if path.exists():
# Transformers metadata
if hf_metadata is not None:
metadata = json.loads(open(path, 'r').read())
if 'max_position_embeddings' in metadata:
model_settings['truncation_length'] = metadata['max_position_embeddings']

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@ -241,6 +241,8 @@ def fix_loader_name(name):
return 'ctransformers'
elif name in ['autoawq', 'awq', 'auto-awq']:
return 'AutoAWQ'
elif name in ['quip#', 'quip-sharp', 'quipsharp', 'quip_sharp']:
return 'QuIP#'
def add_extension(name, last=False):