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https://github.com/turboderp-org/exllamav2.git
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63 lines
1.4 KiB
Python
63 lines
1.4 KiB
Python
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import sys, os
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from exllamav2 import(
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ExLlamaV2,
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ExLlamaV2Config,
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ExLlamaV2Cache,
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ExLlamaV2Tokenizer,
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)
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from exllamav2.generator import (
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ExLlamaV2BaseGenerator,
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ExLlamaV2Sampler
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)
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import time
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# Initialize model and cache
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model_directory = "/mnt/str/models/mistral-7b-instruct-exl2/4.0bpw/"
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config = ExLlamaV2Config()
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config.model_dir = model_directory
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config.prepare()
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model = ExLlamaV2(config)
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print("Loading model: " + model_directory)
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cache = ExLlamaV2Cache(model, lazy = True)
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model.load_autosplit(cache)
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tokenizer = ExLlamaV2Tokenizer(config)
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# Initialize generator
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generator = ExLlamaV2BaseGenerator(model, cache, tokenizer)
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# Generate some text
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settings = ExLlamaV2Sampler.Settings()
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settings.temperature = 0.85
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settings.top_k = 50
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settings.top_p = 0.8
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settings.token_repetition_penalty = 1.05
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settings.disallow_tokens(tokenizer, [tokenizer.eos_token_id])
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prompt = "Our story begins in the Scottish town of Auchtermuchty, where once"
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max_new_tokens = 150
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generator.warmup()
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time_begin = time.time()
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output = generator.generate_simple(prompt, settings, max_new_tokens, seed = 1234)
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time_end = time.time()
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time_total = time_end - time_begin
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print(output)
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print()
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print(f"Response generated in {time_total:.2f} seconds, {max_new_tokens} tokens, {max_new_tokens / time_total:.2f} tokens/second")
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