Spaces:
Runtime error
Runtime error
File size: 4,979 Bytes
5bb42f0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 |
#!/usr/bin/env python3
import requests
HOST = '0.0.0.0:5000'
def generate(prompt, tokens=200):
request = {'prompt': prompt, 'max_new_tokens': tokens}
response = requests.post(f'http://{HOST}/api/v1/generate', json=request)
if response.status_code == 200:
return response.json()['results'][0]['text']
def model_api(request):
response = requests.post(f'http://{HOST}/api/v1/model', json=request)
return response.json()
# print some common settings
def print_basic_model_info(response):
basic_settings = ['truncation_length', 'instruction_template']
print("Model: ", response['result']['model_name'])
print("Lora(s): ", response['result']['lora_names'])
for setting in basic_settings:
print(setting, "=", response['result']['shared.settings'][setting])
# model info
def model_info():
response = model_api({'action': 'info'})
print_basic_model_info(response)
# simple loader
def model_load(model_name):
return model_api({'action': 'load', 'model_name': model_name})
# complex loader
def complex_model_load(model):
def guess_groupsize(model_name):
if '1024g' in model_name:
return 1024
elif '128g' in model_name:
return 128
elif '32g' in model_name:
return 32
else:
return -1
req = {
'action': 'load',
'model_name': model,
'args': {
'loader': 'AutoGPTQ',
'bf16': False,
'load_in_8bit': False,
'groupsize': 0,
'wbits': 0,
# llama.cpp
'threads': 0,
'n_batch': 512,
'no_mmap': False,
'mlock': False,
'cache_capacity': None,
'n_gpu_layers': 0,
'n_ctx': 2048,
# RWKV
'rwkv_strategy': None,
'rwkv_cuda_on': False,
# b&b 4-bit
# 'load_in_4bit': False,
# 'compute_dtype': 'float16',
# 'quant_type': 'nf4',
# 'use_double_quant': False,
# "cpu": false,
# "auto_devices": false,
# "gpu_memory": null,
# "cpu_memory": null,
# "disk": false,
# "disk_cache_dir": "cache",
},
}
model = model.lower()
if '4bit' in model or 'gptq' in model or 'int4' in model:
req['args']['wbits'] = 4
req['args']['groupsize'] = guess_groupsize(model)
elif '3bit' in model:
req['args']['wbits'] = 3
req['args']['groupsize'] = guess_groupsize(model)
else:
req['args']['gptq_for_llama'] = False
if '8bit' in model:
req['args']['load_in_8bit'] = True
elif '-hf' in model or 'fp16' in model:
if '7b' in model:
req['args']['bf16'] = True # for 24GB
elif '13b' in model:
req['args']['load_in_8bit'] = True # for 24GB
elif 'ggml' in model:
# req['args']['threads'] = 16
if '7b' in model:
req['args']['n_gpu_layers'] = 100
elif '13b' in model:
req['args']['n_gpu_layers'] = 100
elif '30b' in model or '33b' in model:
req['args']['n_gpu_layers'] = 59 # 24GB
elif '65b' in model:
req['args']['n_gpu_layers'] = 42 # 24GB
elif 'rwkv' in model:
req['args']['rwkv_cuda_on'] = True
if '14b' in model:
req['args']['rwkv_strategy'] = 'cuda f16i8' # 24GB
else:
req['args']['rwkv_strategy'] = 'cuda f16' # 24GB
return model_api(req)
if __name__ == '__main__':
for model in model_api({'action': 'list'})['result']:
try:
resp = complex_model_load(model)
if 'error' in resp:
print(f"❌ {model} FAIL Error: {resp['error']['message']}")
continue
else:
print_basic_model_info(resp)
ans = generate("0,1,1,2,3,5,8,13,", tokens=2)
if '21' in ans:
print(f"✅ {model} PASS ({ans})")
else:
print(f"❌ {model} FAIL ({ans})")
except Exception as e:
print(f"❌ {model} FAIL Exception: {repr(e)}")
# 0,1,1,2,3,5,8,13, is the fibonacci sequence, the next number is 21.
# Some results below.
""" $ ./model-api-example.py
Model: 4bit_gpt4-x-alpaca-13b-native-4bit-128g-cuda
Lora(s): []
truncation_length = 2048
instruction_template = Alpaca
✅ 4bit_gpt4-x-alpaca-13b-native-4bit-128g-cuda PASS (21)
Model: 4bit_WizardLM-13B-Uncensored-4bit-128g
Lora(s): []
truncation_length = 2048
instruction_template = WizardLM
✅ 4bit_WizardLM-13B-Uncensored-4bit-128g PASS (21)
Model: Aeala_VicUnlocked-alpaca-30b-4bit
Lora(s): []
truncation_length = 2048
instruction_template = Alpaca
✅ Aeala_VicUnlocked-alpaca-30b-4bit PASS (21)
Model: alpaca-30b-4bit
Lora(s): []
truncation_length = 2048
instruction_template = Alpaca
✅ alpaca-30b-4bit PASS (21)
"""
|