Merge pull request #206 from oobabooga/llama-4bit

Add LLaMA 4-bit support
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oobabooga 2023-03-09 21:07:32 -03:00 committed by GitHub
commit 1a3d25f75d
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3 changed files with 26 additions and 1 deletions

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@ -138,6 +138,7 @@ Optionally, you can use the following command-line flags:
| `--cai-chat` | Launch the web UI in chat mode with a style similar to Character.AI's. If the file `img_bot.png` or `img_bot.jpg` exists in the same folder as server.py, this image will be used as the bot's profile picture. Similarly, `img_me.png` or `img_me.jpg` will be used as your profile picture. |
| `--cpu` | Use the CPU to generate text.|
| `--load-in-8bit` | Load the model with 8-bit precision.|
| `--load-in-4bit` | Load the model with 4-bit precision. Currently only works with LLaMA. |
| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
| `--auto-devices` | Automatically split the model across the available GPU(s) and CPU.|
| `--disk` | If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk. |

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@ -1,5 +1,6 @@
import json
import os
import sys
import time
import zipfile
from pathlib import Path
@ -41,7 +42,7 @@ def load_model(model_name):
shared.is_RWKV = model_name.lower().startswith('rwkv-')
# Default settings
if not (shared.args.cpu or shared.args.load_in_8bit or shared.args.auto_devices or shared.args.disk or shared.args.gpu_memory is not None or shared.args.cpu_memory is not None or shared.args.deepspeed or shared.args.flexgen or shared.is_RWKV):
if not (shared.args.cpu or shared.args.load_in_8bit or shared.args.load_in_4bit or shared.args.auto_devices or shared.args.disk or shared.args.gpu_memory is not None or shared.args.cpu_memory is not None or shared.args.deepspeed or shared.args.flexgen or shared.is_RWKV):
if any(size in shared.model_name.lower() for size in ('13b', '20b', '30b')):
model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), device_map='auto', load_in_8bit=True)
else:
@ -86,6 +87,28 @@ def load_model(model_name):
return model, tokenizer
# 4-bit LLaMA
elif shared.args.load_in_4bit:
sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa")))
from llama import load_quant
path_to_model = Path(f'models/{model_name}')
pt_model = ''
if path_to_model.name.lower().startswith('llama-7b'):
pt_model = 'llama-7b-4bit.pt'
if path_to_model.name.lower().startswith('llama-13b'):
pt_model = 'llama-13b-4bit.pt'
if path_to_model.name.lower().startswith('llama-30b'):
pt_model = 'llama-30b-4bit.pt'
if not Path(f"models/{pt_model}").exists():
print(f"Could not find models/{pt_model}, exiting...")
exit()
model = load_quant(path_to_model, Path(f"models/{pt_model}"), 4)
model = model.to(torch.device('cuda:0'))
# Custom
else:
command = "AutoModelForCausalLM.from_pretrained"

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@ -68,6 +68,7 @@ parser.add_argument('--chat', action='store_true', help='Launch the web UI in ch
parser.add_argument('--cai-chat', action='store_true', help='Launch the web UI in chat mode with a style similar to Character.AI\'s. If the file img_bot.png or img_bot.jpg exists in the same folder as server.py, this image will be used as the bot\'s profile picture. Similarly, img_me.png or img_me.jpg will be used as your profile picture.')
parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text.')
parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision.')
parser.add_argument('--load-in-4bit', action='store_true', help='Load the model with 4-bit precision. Currently only works with LLaMA.')
parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.')
parser.add_argument('--disk', action='store_true', help='If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk.')