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Replace --load-in-4bit with --llama-bits

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Replaces --load-in-4bit with a more flexible --llama-bits arg to allow for 2 and 3 bit models as well. This commit also fixes a loading issue with .pt files which are not in the root of the models folder
This commit is contained in:
draff 2023-03-10 21:36:45 +00:00
parent 026d60bd34
commit e6c631aea4
3 changed files with 11 additions and 10 deletions
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2
README.md
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@ -138,7 +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. | | `--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.| | `--cpu` | Use the CPU to generate text.|
| `--load-in-8bit` | Load the model with 8-bit precision.| | `--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. | | `--llama-bits` | Load LLaMA models with specified precision. 2, 3 and 4 bit are supported, use standard `--load-in-8bit` for 8bit precision. |
| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. | | `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
| `--auto-devices` | Automatically split the model across the available GPU(s) and CPU.| | `--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. | | `--disk` | If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk. |

17
modules/models.py
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@ -42,7 +42,7 @@ def load_model(model_name):
shared.is_RWKV = model_name.lower().startswith('rwkv-') shared.is_RWKV = model_name.lower().startswith('rwkv-')
# Default settings # Default settings
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 not (shared.args.cpu or shared.args.load_in_8bit or shared.args.llama_bits>0 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')): 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) model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), device_map='auto', load_in_8bit=True)
else: else:
@ -88,23 +88,24 @@ def load_model(model_name):
return model, tokenizer return model, tokenizer
# 4-bit LLaMA # 4-bit LLaMA
elif shared.args.load_in_4bit: elif shared.args.llama_bits>0:
sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa"))) sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa")))
bits = shared.args.llama_bits
from llama import load_quant from llama import load_quant
path_to_model = Path(f'models/{model_name}') path_to_model = Path(f'models/{model_name}')
pt_model = '' pt_model = ''
if path_to_model.name.lower().startswith('llama-7b'): if path_to_model.name.lower().startswith('llama-7b'):
pt_model = 'llama-7b-4bit.pt' pt_model = f'llama-7b-{bits}bit.pt'
elif path_to_model.name.lower().startswith('llama-13b'): elif path_to_model.name.lower().startswith('llama-13b'):
pt_model = 'llama-13b-4bit.pt' pt_model = f'llama-13b-{bits}bit.pt'
elif path_to_model.name.lower().startswith('llama-30b'): elif path_to_model.name.lower().startswith('llama-30b'):
pt_model = 'llama-30b-4bit.pt' pt_model = f'llama-30b-{bits}bit.pt'
elif path_to_model.name.lower().startswith('llama-65b'): elif path_to_model.name.lower().startswith('llama-65b'):
pt_model = 'llama-65b-4bit.pt' pt_model = f'llama-65b-{bits}bit.pt'
else: else:
pt_model = f'{model_name}-4bit.pt' pt_model = f'{model_name}-{bits}bit.pt'
# Try to find the .pt both in models/ and in the subfolder # Try to find the .pt both in models/ and in the subfolder
pt_path = None pt_path = None
@ -116,7 +117,7 @@ def load_model(model_name):
print(f"Could not find {pt_model}, exiting...") print(f"Could not find {pt_model}, exiting...")
exit() exit()
model = load_quant(path_to_model, Path(f"models/{pt_model}"), 4) model = load_quant(path_to_model, Path(f"{pt_path}"), bits)
# Multi-GPU setup # Multi-GPU setup
if shared.args.gpu_memory: if shared.args.gpu_memory:

2
modules/shared.py
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@ -67,7 +67,7 @@ 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('--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('--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-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('--llama-bits', type=int, default=0, help='Load LLaMA models with specified precision. 2, 3 and 4 bit are supported, use standard `--load-in-8bit` for 8bit precision.')
parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.') 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('--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.') 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.')