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Merge branch 'oobabooga:main' into lora-and-model-dir

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catalpaaa 2023-03-25 01:28:33 -07:00 committed by GitHub
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2
README.md
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@ -27,7 +27,7 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.
* [FlexGen offload](https://github.com/oobabooga/text-generation-webui/wiki/FlexGen). * [FlexGen offload](https://github.com/oobabooga/text-generation-webui/wiki/FlexGen).
* [DeepSpeed ZeRO-3 offload](https://github.com/oobabooga/text-generation-webui/wiki/DeepSpeed). * [DeepSpeed ZeRO-3 offload](https://github.com/oobabooga/text-generation-webui/wiki/DeepSpeed).
* Get responses via API, [with](https://github.com/oobabooga/text-generation-webui/blob/main/api-example-streaming.py) or [without](https://github.com/oobabooga/text-generation-webui/blob/main/api-example.py) streaming. * Get responses via API, [with](https://github.com/oobabooga/text-generation-webui/blob/main/api-example-streaming.py) or [without](https://github.com/oobabooga/text-generation-webui/blob/main/api-example.py) streaming.
* [LLaMA model, including 4-bit mode](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model). * [LLaMA model, including 4-bit GPTQ support](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model).
* [RWKV model](https://github.com/oobabooga/text-generation-webui/wiki/RWKV-model). * [RWKV model](https://github.com/oobabooga/text-generation-webui/wiki/RWKV-model).
* [Supports LoRAs](https://github.com/oobabooga/text-generation-webui/wiki/Using-LoRAs). * [Supports LoRAs](https://github.com/oobabooga/text-generation-webui/wiki/Using-LoRAs).
* Supports softprompts. * Supports softprompts.

16
modules/GPTQ_loader.py
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@ -37,21 +37,23 @@ def load_quantized(model_name):
path_to_model = Path(f'models/{model_name}') path_to_model = Path(f'models/{model_name}')
if path_to_model.name.lower().startswith('llama-7b'): if path_to_model.name.lower().startswith('llama-7b'):
pt_model = f'llama-7b-{shared.args.gptq_bits}bit.pt' pt_model = f'llama-7b-{shared.args.gptq_bits}bit'
elif path_to_model.name.lower().startswith('llama-13b'): elif path_to_model.name.lower().startswith('llama-13b'):
pt_model = f'llama-13b-{shared.args.gptq_bits}bit.pt' pt_model = f'llama-13b-{shared.args.gptq_bits}bit'
elif path_to_model.name.lower().startswith('llama-30b'): elif path_to_model.name.lower().startswith('llama-30b'):
pt_model = f'llama-30b-{shared.args.gptq_bits}bit.pt' pt_model = f'llama-30b-{shared.args.gptq_bits}bit'
elif path_to_model.name.lower().startswith('llama-65b'): elif path_to_model.name.lower().startswith('llama-65b'):
pt_model = f'llama-65b-{shared.args.gptq_bits}bit.pt' pt_model = f'llama-65b-{shared.args.gptq_bits}bit'
else: else:
pt_model = f'{model_name}-{shared.args.gptq_bits}bit.pt' pt_model = f'{model_name}-{shared.args.gptq_bits}bit'
# Try to find the .pt both in models/ and in the subfolder # Try to find the .safetensors or .pt both in models/ and in the subfolder
pt_path = None pt_path = None
for path in [Path(p) for p in [f"models/{pt_model}", f"{path_to_model}/{pt_model}"]]: for path in [Path(p+ext) for ext in ['.safetensors', '.pt'] for p in [f"models/{pt_model}", f"{path_to_model}/{pt_model}"]]:
if path.exists(): if path.exists():
print(f"Found {path}")
pt_path = path pt_path = path
break
if not pt_path: if not pt_path:
print(f"Could not find {pt_model}, exiting...") print(f"Could not find {pt_model}, exiting...")

8
modules/LoRA.py
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@ -1,5 +1,7 @@
from pathlib import Path from pathlib import Path
import torch
import modules.shared as shared import modules.shared as shared
from modules.models import load_model from modules.models import load_model
from modules.text_generation import clear_torch_cache from modules.text_generation import clear_torch_cache
@ -34,4 +36,8 @@ def add_lora_to_model(lora_name):
if not shared.args.load_in_8bit and not shared.args.cpu: if not shared.args.load_in_8bit and not shared.args.cpu:
shared.model.half() shared.model.half()
if not hasattr(shared.model, "hf_device_map"): if not hasattr(shared.model, "hf_device_map"):
shared.model.cuda() if torch.has_mps:
device = torch.device('mps')
shared.model = shared.model.to(device)
else:
shared.model = shared.model.cuda()