Split nodes into files, allow loading each separately without cloning the repo, some other minor stuff, install exllamav2 pip package by default
This commit is contained in:
@@ -8,10 +8,7 @@ git clone https://github.com/Zuellni/ComfyUI-ExLlama-Nodes
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pip install -r requirements.txt
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```
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If you see any ExLlama-related errors while loading, install it manually from [here](https://github.com/turboderp/exllamav2/releases/latest). For example, on Windows with Python 3.10 and CUDA 11.7:
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```
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pip install https://github.com/turboderp/exllamav2/releases/download/v0.0.4/exllamav2-0.0.4+cu117-cp310-cp310-win_amd64.whl
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```
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If you see any ExLlama-related errors while loading, install it manually following the instructions from [here](https://github.com/turboderp/exllamav2#installation).
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## Nodes
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Name | Description
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+7
-15
@@ -1,17 +1,9 @@
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from .nodes import Generator, Loader, Previewer, Replacer
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NODE_CLASS_MAPPINGS = {
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"ZuellniExLlamaLoader": Loader,
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"ZuellniExLlamaGenerator": Generator,
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"ZuellniTextPreviewer": Previewer,
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"ZuellniTextReplacer": Replacer,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ZuellniExLlamaLoader": "ExLlama Loader",
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"ZuellniExLlamaGenerator": "ExLlama Generator",
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"ZuellniTextPreviewer": "Preview Text",
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"ZuellniTextReplacer": "Replace Text",
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}
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from . import exllama, text
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NODE_CLASS_MAPPINGS = {}
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NODE_DISPLAY_NAME_MAPPINGS = {}
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WEB_DIRECTORY = "."
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for module in (exllama, text):
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NODE_CLASS_MAPPINGS.update(module.NODE_CLASS_MAPPINGS)
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NODE_DISPLAY_NAME_MAPPINGS.update(module.NODE_DISPLAY_NAME_MAPPINGS)
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+122
@@ -0,0 +1,122 @@
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from time import time
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import torch
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from comfy.utils import ProgressBar
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from exllamav2 import ExLlamaV2, ExLlamaV2Cache, ExLlamaV2Config, ExLlamaV2Tokenizer
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from exllamav2.generator import ExLlamaV2Sampler, ExLlamaV2StreamingGenerator
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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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"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 = ("EL_MODEL",)
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def load(self, model_dir, max_seq_len):
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config = ExLlamaV2Config()
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config.model_dir = model_dir
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config.prepare()
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config.max_seq_len = max_seq_len
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model = ExLlamaV2(config)
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model.load()
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cache = ExLlamaV2Cache(model)
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tokenizer = ExLlamaV2Tokenizer(config)
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generator = ExLlamaV2StreamingGenerator(model, cache, tokenizer)
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settings = ExLlamaV2Sampler.Settings()
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return ((tokenizer, generator, settings),)
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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": ("EL_MODEL",),
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"stop_on_newline": ((False, True),),
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"max_tokens": ("INT", {"default": 128, "min": 1, "max": 8192}),
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"temperature": ("FLOAT", {"default": 0.7, "max": 2, "step": 0.01}),
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"top_k": ("INT", {"default": 20, "max": 200}),
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"top_p": ("FLOAT", {"default": 0.9, "max": 1, "step": 0.01}),
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"typical": ("FLOAT", {"default": 1, "max": 1, "step": 0.01}),
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"penalty": ("FLOAT", {"default": 1.15, "min": 1, "max": 2, "step": 0.01}),
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"seed": ("INT", {"max": 2**64 - 1}),
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"text": ("STRING", {"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(
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self,
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model,
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stop_on_newline,
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max_tokens,
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temperature,
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top_k,
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top_p,
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typical,
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penalty,
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seed,
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text,
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):
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tokenizer, generator, settings = model
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progress = ProgressBar(max_tokens)
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if not text:
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return ("",)
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prompt = tokenizer.encode(text)
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stop_conditions = [tokenizer.eos_token_id]
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stop_on_newline and stop_conditions.append(tokenizer.newline_token_id)
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generator.set_stop_conditions(stop_conditions)
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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
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settings.token_repetition_penalty = penalty
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torch.manual_seed(seed)
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generator.begin_stream(prompt, settings)
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start = time()
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eos = False
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output = ""
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tokens = 0
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while not eos and tokens < max_tokens:
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chunk, eos, _ = generator.stream()
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progress.update(1)
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output += chunk
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tokens += 1
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total = round(time() - start, 2)
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speed = round(tokens / total, 2)
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print(f"Output generated in {total} seconds ({tokens} tokens, {speed} tokens/s)")
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return (output.strip(),)
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NODE_CLASS_MAPPINGS = {
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"ZuellniExLlamaLoader": Loader,
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"ZuellniExLlamaGenerator": Generator,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ZuellniExLlamaLoader": "Loader",
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"ZuellniExLlamaGenerator": "Generator",
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}
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@@ -1,157 +0,0 @@
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import torch
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from comfy.utils import ProgressBar
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from exllamav2 import ExLlamaV2, ExLlamaV2Cache, ExLlamaV2Config, ExLlamaV2Tokenizer
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from exllamav2.generator import ExLlamaV2Sampler, ExLlamaV2StreamingGenerator
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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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"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 = ("EXLLAMA_MODEL",)
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def load(self, model_dir, max_seq_len):
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config = ExLlamaV2Config()
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config.model_dir = model_dir
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config.prepare()
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config.max_seq_len = max_seq_len
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model = ExLlamaV2(config)
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model.load()
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tokenizer = ExLlamaV2Tokenizer(config)
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cache = ExLlamaV2Cache(model)
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generator = ExLlamaV2StreamingGenerator(model, cache, tokenizer)
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return (generator,)
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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": ("EXLLAMA_MODEL",),
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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, "max": 2, "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, "max": 1, "step": 0.01}),
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"typical": ("FLOAT", {"default": 1, "min": 0, "max": 1, "step": 0.01}),
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"penalty": ("FLOAT", {"default": 1.15, "min": 1, "max": 2, "step": 0.01}),
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"seed": ("INT", {"default": 0, "min": 0, "max": 2**64 - 1}),
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"text": ("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(
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self,
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model,
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stop_on_newline,
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max_tokens,
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temperature,
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top_k,
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top_p,
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typical,
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penalty,
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seed,
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text,
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):
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torch.manual_seed(seed)
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progress = ProgressBar(max_tokens)
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prompt = model.tokenizer.encode(text)
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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 += [model.tokenizer.newline_token_id]
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settings = ExLlamaV2Sampler.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
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settings.token_repetition_penalty = penalty
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model.set_stop_conditions(stop_conditions)
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model.begin_stream(prompt, settings)
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eos = False
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tokens = 0
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text = ""
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while not eos and tokens < max_tokens:
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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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tokens += 1
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return (text.strip(),)
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class Previewer:
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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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"text": ("STRING", {"forceInput": True}),
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},
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"hidden": {
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"info": "EXTRA_PNGINFO",
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"id": "UNIQUE_ID",
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},
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}
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CATEGORY = "Zuellni/Text"
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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, info=None, id=None):
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if id and info and "workflow" in info:
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nodes = info["workflow"]["nodes"]
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node = next((n for n in nodes if str(n["id"]) == id), None)
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if node:
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node["widgets_values"] = [text]
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return {"ui": {"text": [text]}}
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class Replacer:
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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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"text": ("STRING", {"default": "", "multiline": True}),
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},
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"optional": {
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"a": ("STRING", {"forceInput": True, "multiline": True}),
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"b": ("STRING", {"forceInput": True, "multiline": True}),
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"c": ("STRING", {"forceInput": True, "multiline": True}),
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"d": ("STRING", {"forceInput": True, "multiline": True}),
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}
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}
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CATEGORY = "Zuellni/Text"
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FUNCTION = "replace"
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RETURN_NAMES = ("TEXT",)
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RETURN_TYPES = ("STRING",)
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def replace(self, text, **vars):
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for key, value, in vars.items():
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text = text.replace(f"[{key}]", value)
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return (text,)
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+1
-4
@@ -1,4 +1 @@
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https://github.com/turboderp/exllamav2/releases/download/v0.0.5/exllamav2-0.0.5+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
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https://github.com/turboderp/exllamav2/releases/download/v0.0.5/exllamav2-0.0.5+cu118-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
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https://github.com/turboderp/exllamav2/releases/download/v0.0.5/exllamav2-0.0.5+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and python_version == "3.11"
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https://github.com/turboderp/exllamav2/releases/download/v0.0.5/exllamav2-0.0.5+cu118-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and python_version == "3.10"
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exllamav2
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@@ -0,0 +1,67 @@
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class Previewer:
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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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"text": ("STRING", {"forceInput": True}),
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},
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"hidden": {
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"info": "EXTRA_PNGINFO",
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"id": "UNIQUE_ID",
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},
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}
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CATEGORY = "Zuellni/Text"
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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, info=None, id=None):
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if id and info and "workflow" in info:
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nodes = info["workflow"]["nodes"]
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node = next((n for n in nodes if str(n["id"]) == id), None)
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if node:
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node["widgets_values"] = [text]
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return {"ui": {"text": [text]}}
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class Replacer:
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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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"text": ("STRING", {"multiline": True}),
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},
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"optional": {
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"a": ("STRING", {"forceInput": True, "multiline": True}),
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"b": ("STRING", {"forceInput": True, "multiline": True}),
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"c": ("STRING", {"forceInput": True, "multiline": True}),
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"d": ("STRING", {"forceInput": True, "multiline": True}),
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},
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}
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CATEGORY = "Zuellni/Text"
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FUNCTION = "replace"
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RETURN_NAMES = ("TEXT",)
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RETURN_TYPES = ("STRING",)
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def replace(self, text, **vars):
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for key, value in vars.items():
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text = text.replace(f"[{key}]", value)
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return (text,)
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NODE_CLASS_MAPPINGS = {
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"ZuellniTextPreviewer": Previewer,
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"ZuellniTextReplacer": Replacer,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ZuellniTextPreviewer": "Preview Text",
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"ZuellniTextReplacer": "Replace Text",
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}
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WEB_DIRECTORY = "."
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Reference in New Issue
Block a user