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Merge pull request #206 from oobabooga/llama-4bit
Add LLaMA 4-bit support
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1a3d25f75d
@ -138,6 +138,7 @@ Optionally, you can use the following command-line flags:
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| `--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. |
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| `--cpu` | Use the CPU to generate text.|
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| `--load-in-8bit` | Load the model with 8-bit precision.|
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| `--load-in-4bit` | Load the model with 4-bit precision. Currently only works with LLaMA. |
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| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
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| `--auto-devices` | Automatically split the model across the available GPU(s) and CPU.|
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| `--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 @@
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import json
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import os
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import sys
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import time
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import zipfile
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from pathlib import Path
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@ -41,7 +42,7 @@ def load_model(model_name):
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shared.is_RWKV = model_name.lower().startswith('rwkv-')
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# Default settings
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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):
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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):
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if any(size in shared.model_name.lower() for size in ('13b', '20b', '30b')):
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model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), device_map='auto', load_in_8bit=True)
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else:
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@ -86,6 +87,28 @@ def load_model(model_name):
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return model, tokenizer
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# 4-bit LLaMA
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elif shared.args.load_in_4bit:
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sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa")))
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from llama import load_quant
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path_to_model = Path(f'models/{model_name}')
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pt_model = ''
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if path_to_model.name.lower().startswith('llama-7b'):
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pt_model = 'llama-7b-4bit.pt'
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if path_to_model.name.lower().startswith('llama-13b'):
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pt_model = 'llama-13b-4bit.pt'
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if path_to_model.name.lower().startswith('llama-30b'):
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pt_model = 'llama-30b-4bit.pt'
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if not Path(f"models/{pt_model}").exists():
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print(f"Could not find models/{pt_model}, exiting...")
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exit()
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model = load_quant(path_to_model, Path(f"models/{pt_model}"), 4)
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model = model.to(torch.device('cuda:0'))
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# Custom
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else:
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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
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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.')
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parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text.')
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parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision.')
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parser.add_argument('--load-in-4bit', action='store_true', help='Load the model with 4-bit precision. Currently only works with LLaMA.')
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parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
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parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.')
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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.')
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