mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-10-01 01:26:03 -04:00
82 lines
3.1 KiB
Python
82 lines
3.1 KiB
Python
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path("repositories/exllama")))
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from modules.logging_colors import logger
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from repositories.exllama.generator import ExLlamaGenerator
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from repositories.exllama.model import ExLlama, ExLlamaCache, ExLlamaConfig
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from repositories.exllama.tokenizer import ExLlamaTokenizer
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class ExllamaModel:
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def __init__(self):
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pass
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@classmethod
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def from_pretrained(self, path_to_model):
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path_to_model = Path("models") / Path(path_to_model)
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tokenizer_model_path = path_to_model / "tokenizer.model"
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model_config_path = path_to_model / "config.json"
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# Find the model checkpoint
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model_path = None
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for ext in ['.safetensors', '.pt', '.bin']:
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found = list(path_to_model.glob(f"*{ext}"))
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if len(found) > 0:
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if len(found) > 1:
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logger.warning(f'More than one {ext} model has been found. The last one will be selected. It could be wrong.')
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model_path = found[-1]
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break
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config = ExLlamaConfig(str(model_config_path))
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config.model_path = str(model_path)
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model = ExLlama(config)
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tokenizer = ExLlamaTokenizer(str(tokenizer_model_path))
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cache = ExLlamaCache(model)
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result = self()
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result.config = config
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result.model = model
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result.cache = cache
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result.tokenizer = tokenizer
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return result, result
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def generate(self, prompt, state, callback=None):
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generator = ExLlamaGenerator(self.model, self.tokenizer, self.cache)
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generator.settings.temperature = state['temperature']
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generator.settings.top_p = state['top_p']
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generator.settings.top_k = state['top_k']
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generator.settings.typical = state['typical_p']
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generator.settings.token_repetition_penalty_max = state['repetition_penalty']
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if state['ban_eos_token']:
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generator.disallow_tokens([self.tokenizer.eos_token_id])
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text = generator.generate_simple(prompt, max_new_tokens=state['max_new_tokens'])
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return text
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def generate_with_streaming(self, prompt, state, callback=None):
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generator = ExLlamaGenerator(self.model, self.tokenizer, self.cache)
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generator.settings.temperature = state['temperature']
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generator.settings.top_p = state['top_p']
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generator.settings.top_k = state['top_k']
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generator.settings.typical = state['typical_p']
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generator.settings.token_repetition_penalty_max = state['repetition_penalty']
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if state['ban_eos_token']:
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generator.disallow_tokens([self.tokenizer.eos_token_id])
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generator.end_beam_search()
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ids = generator.tokenizer.encode(prompt)
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generator.gen_begin(ids)
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initial_len = generator.sequence[0].shape[0]
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for i in range(state['max_new_tokens']):
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token = generator.gen_single_token()
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yield (generator.tokenizer.decode(generator.sequence[0][initial_len:]))
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if token.item() == generator.tokenizer.eos_token_id:
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break
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def encode(self, string, **kwargs):
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return self.tokenizer.encode(string)
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