Spaces:
Sleeping
Sleeping
File size: 3,135 Bytes
dc54faf c34df49 56abc69 70b610d c34df49 69c15f2 c34df49 6e9cf31 c34df49 70b610d dc54faf c34df49 d061b72 c673c9d c34df49 c673c9d c34df49 ebaf7f4 70b610d 9838c31 70b610d c34df49 9838c31 c34df49 9838c31 c34df49 9838c31 dc54faf c34df49 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
import gradio as gr
from gpt4all import GPT4All
from huggingface_hub import hf_hub_download
import faiss
#from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_huggingface import HuggingFaceEmbeddings
import numpy as np
from pypdf import PdfReader
from gradio_pdf import PDF
from pdf2image import convert_from_path
from transformers import pipeline
from pathlib import Path
from langchain_chroma import Chroma
title = "Mistral-7B-Instruct-GGUF Run On CPU-Basic Free Hardware"
description = """
🔎 [Mistral AI's Mistral 7B Instruct v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) [GGUF format model](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF) , 4-bit quantization balanced quality gguf version, running on CPU. English Only (Also support other languages but the quality's not good). Using [GitHub - llama.cpp](https://github.com/ggerganov/llama.cpp) [GitHub - gpt4all](https://github.com/nomic-ai/gpt4all).
🔨 Running on CPU-Basic free hardware. Suggest duplicating this space to run without a queue.
Mistral does not support system prompt symbol (such as ```<<SYS>>```) now, input your system prompt in the first message if you need. Learn more: [Guardrailing Mistral 7B](https://docs.mistral.ai/usage/guardrailing).
"""
"""
[Model From TheBloke/Mistral-7B-Instruct-v0.1-GGUF](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF)
[Mistral-instruct-v0.1 System prompt](https://docs.mistral.ai/usage/guardrailing)
"""
model_path = "models"
model_name = "mistral-7b-instruct-v0.1.Q4_K_M.gguf"
hf_hub_download(repo_id="TheBloke/Mistral-7B-Instruct-v0.1-GGUF", filename=model_name, local_dir=model_path, local_dir_use_symlinks=False)
print("Start the model init process")
model = model = GPT4All(model_name, model_path, allow_download = False, device="cpu")
model.config["promptTemplate"] = "[INST] {0} [/INST]"
model.config["systemPrompt"] = "Tu es un assitant et tu dois répondre en français"
model._is_chat_session_activated = False
max_new_tokens = 2048
model_kwargs = {'device': 'cpu'}
encode_kwargs = {'normalize_embeddings': False}
embeddings = HuggingFaceEmbeddings(
model_kwargs=model_kwargs,
encode_kwargs=encode_kwargs
)
chunk_size = 2048
# creating a pdf reader object
print("Finish the model init process")
def extract_text(file):
reader = PdfReader(file)
text = []
for p in np.arange(0, len(reader.pages), 1):
page = reader.pages[int(p)]
# extracting text from page
text.append(page.extract_text())
text = ' '.join(text)
return text
def summarise(text):
chunks = [text[i:i + chunk_size] for i in range(0, len(text), chunk_size)]
return print(len(len(chunks)))
with gr.Blocks() as demo:
file_input = gr.File(label="Upload a PDF file")
text_output = gr.Textbox(label="Extracted Text")
summary_output = gr.Textbox(label="Summary")
file_input.upload(extract_text, inputs=file_input, outputs=text_output)
text_output.change(summarise,text_output,summary_output)
if __name__ == "__main__":
demo.queue(max_size=3).launch() |