120 lines
3.9 KiB
Python
120 lines
3.9 KiB
Python
from pathlib import Path
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import torch
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from comfy.utils import ProgressBar
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from comfy.model_management import soft_empty_cache
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from exllama.alt_generator import ExLlamaAltGenerator
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from exllama.lora import ExLlamaLora
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from exllama.model import ExLlama, ExLlamaCache, ExLlamaConfig
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from exllama.tokenizer import ExLlamaTokenizer
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class Generator:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"model": ("GPTQ",),
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"stop_on_newline": ([False, True], {"default": False}),
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"max_tokens": ("INT", {"default": 128, "min": 1, "max": 8192}),
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"temperature": ("FLOAT", {"default": 0.7, "min": 0.0, "max": 2.0, "step": 0.01}),
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"top_k": ("INT", {"default": 20, "min": 0, "max": 200}),
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"top_p": ("FLOAT", {"default": 0.9, "min": 0.0, "max": 1.0, "step": 0.01}),
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"typical_p": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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"penalty": ("FLOAT", {"default": 1.15, "min": 1.0, "max": 2.0, "step": 0.01}),
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"seed": ("INT", {"default": 0, "min": 0, "max": 2**64 - 1}),
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"prompt": ("STRING", {"default": "", "multiline": True}),
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},
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}
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CATEGORY = "Zuellni/ExLlama"
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FUNCTION = "generate"
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RETURN_NAMES = ("TEXT",)
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RETURN_TYPES = ("STRING",)
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def generate(self, model, stop_on_newline, max_tokens, temperature, top_k, top_p, typical_p, penalty, seed, prompt):
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progress = ProgressBar(max_tokens)
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prompt = prompt.strip()
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torch.manual_seed(seed)
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if not prompt:
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return ("",)
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settings = ExLlamaAltGenerator.Settings()
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settings.temperature = temperature
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settings.top_k = top_k
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settings.top_p = top_p
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settings.typical = typical_p
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settings.token_repetition_penalty_max = penalty
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stop_conditions = [model.tokenizer.eos_token_id]
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if stop_on_newline:
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stop_conditions.append(model.tokenizer.newline_token_id)
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model.begin_stream(prompt, stop_conditions, max_tokens, settings)
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eos = False
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text = ""
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while not eos:
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chunk, eos = model.stream()
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progress.update(1)
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text += chunk
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progress.update_absolute(max_tokens)
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text = text.strip()
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print(text)
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return (text,)
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class Loader:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"model_dir": ("STRING", {"default": ""}),
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"lora_dir": ("STRING", {"default": ""}),
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"max_seq_len": ("INT", {"default": 2048, "min": 1, "max": 8192}),
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},
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}
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CATEGORY = "Zuellni/ExLlama"
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FUNCTION = "load"
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RETURN_NAMES = ("MODEL",)
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RETURN_TYPES = ("GPTQ",)
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def load(self, model_dir, lora_dir, max_seq_len):
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soft_empty_cache()
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model_dir = Path(model_dir).expanduser()
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config = ExLlamaConfig(model_dir / "config.json")
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config.model_path = model_dir.glob("*.safetensors")
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config.max_seq_len = max_seq_len
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model = ExLlama(config)
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cache = ExLlamaCache(model)
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tokenizer = ExLlamaTokenizer(str(model_dir / "tokenizer.model"))
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generator = ExLlamaAltGenerator(model, tokenizer, cache)
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if lora_dir:
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lora_dir = Path(lora_dir).expanduser()
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lora_config = lora_dir / "adapter_config.json"
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lora_model = str(lora_dir / "adapter_model.bin")
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lora = ExLlamaLora(model, lora_config, lora_model)
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generator.lora = lora
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return (generator,)
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class Previewer:
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@classmethod
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def INPUT_TYPES(cls):
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return {"required": {"text": ("STRING", {"forceInput": True})}}
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CATEGORY = "Zuellni/ExLlama"
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FUNCTION = "preview"
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OUTPUT_NODE = True
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RETURN_TYPES = ()
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def preview(self, text):
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return {"ui": {"text": [text]}}
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