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from langchain_community.llms.ctransformers import CTransformers
import os
import gradio as gr
hf_token = os.environ.get('HF_TOKEN')
from huggingface_hub import login
login(token=hf_token)
# config = AutoConfig.from_pretrained("Mistral-7B-v0.1-GGUF")
# config.config.max_new_tokens = 2000
# config.config.context_length = 6000
# llm = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-v0.1-GGUF", model_file="mistral-7b-v0.1.Q5_K_M.gguf", model_type="mistral",gpu_layers=0, config=config)
MODEL_TYPE = 'mistral'
MODEL_BIN_PATH = "mistral-7b-instruct-v0.1.Q3_K_S.gguf"
MAX_NEW_TOKEN = 600
TEMPRATURE = 0.01
CONTEXT_LENGTH = 6000
llm = CTransformers(
model=MODEL_BIN_PATH,
config={
'max_new_tokens': MAX_NEW_TOKEN,
'temperature': TEMPRATURE,
'context_length': CONTEXT_LENGTH
},
model_type=MODEL_TYPE
)
def generate_text(input_text):
output = llm(input_text)
print(output)
return output
text_generation_interface = gr.Interface(
fn=generate_text,
inputs="text", outputs="text")
text_generation_interface.launch() |