mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-22 16:17:57 +01:00
68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
'''
|
|
Based on
|
|
https://github.com/abetlen/llama-cpp-python
|
|
|
|
Documentation:
|
|
https://abetlen.github.io/llama-cpp-python/
|
|
'''
|
|
|
|
from llama_cpp import Llama, LlamaCache
|
|
|
|
from modules import shared
|
|
from modules.callbacks import Iteratorize
|
|
|
|
|
|
class LlamaCppModel:
|
|
def __init__(self):
|
|
self.initialized = False
|
|
|
|
@classmethod
|
|
def from_pretrained(self, path):
|
|
result = self()
|
|
|
|
params = {
|
|
'model_path': str(path),
|
|
'n_ctx': 2048,
|
|
'seed': 0,
|
|
'n_threads': shared.args.threads or None,
|
|
'n_batch': shared.args.n_batch,
|
|
'use_mmap': not shared.args.no_mmap,
|
|
'use_mlock': shared.args.mlock
|
|
}
|
|
self.model = Llama(**params)
|
|
self.model.set_cache(LlamaCache)
|
|
|
|
# This is ugly, but the model and the tokenizer are the same object in this library.
|
|
return result, result
|
|
|
|
def encode(self, string):
|
|
if type(string) is str:
|
|
string = string.encode()
|
|
return self.model.tokenize(string)
|
|
|
|
def generate(self, context="", token_count=20, temperature=1, top_p=1, top_k=50, repetition_penalty=1, callback=None):
|
|
if type(context) is str:
|
|
context = context.encode()
|
|
tokens = self.model.tokenize(context)
|
|
|
|
output = b""
|
|
count = 0
|
|
for token in self.model.generate(tokens, top_k=top_k, top_p=top_p, temp=temperature, repeat_penalty=repetition_penalty):
|
|
text = self.model.detokenize([token])
|
|
output += text
|
|
if callback:
|
|
callback(text.decode())
|
|
|
|
count += 1
|
|
if count >= token_count or (token == self.model.token_eos()):
|
|
break
|
|
|
|
return output.decode()
|
|
|
|
def generate_with_streaming(self, **kwargs):
|
|
with Iteratorize(self.generate, kwargs, callback=None) as generator:
|
|
reply = ''
|
|
for token in generator:
|
|
reply += token
|
|
yield reply
|