Spaces:
Runtime error
Runtime error
File size: 2,657 Bytes
4966832 cc431b5 4966832 4f36f3a 93e2858 bcea1f2 4966832 cc431b5 4966832 cc431b5 4f36f3a 4966832 cc431b5 9589466 4966832 4f36f3a 4966832 cc431b5 4966832 cc431b5 4966832 cc431b5 4966832 cc431b5 4966832 8c07d46 4f36f3a cc431b5 bcea1f2 |
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 |
import gradio as gr
import copy
import time
import llama_cpp
from llama_cpp import Llama
from huggingface_hub import hf_hub_download
import os
from gradio.components import Image, Text
llm = Llama(
model_path=hf_hub_download(
repo_id=os.environ.get("REPO_ID", "TheBloke/Llama-2-7B-Chat-GGML"),
filename=os.environ.get("MODEL_FILE", "llama-2-7b-chat.ggmlv3.q5_0.bin"),
),
n_ctx=2048,
n_gpu_layers=50, # change n_gpu_layers if you have more or less VRAM
)
history = []
system_message = """
You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
"""
def generate_text(message, history):
temp = ""
input_prompt = f"[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n "
for interaction in history:
input_prompt = input_prompt + str(interaction[0]) + " [/INST] " + str(interaction[1]) + " </s><s> [INST] "
input_prompt = input_prompt + str(message) + " [/INST] "
output = llm(
input_prompt,
temperature=0.15,
top_p=0.1,
top_k=40,
repeat_penalty=1.1,
max_tokens=1024,
stop=[
"<|prompter|>",
"<|endoftext|>",
"<|endoftext|> \n",
"ASSISTANT:",
"USER:",
"SYSTEM:",
],
stream=True,
)
for out in output:
stream = copy.deepcopy(out)
temp += stream["choices"][0]["text"]
yield temp
history = ["init", input_prompt]
def predict(img):
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
title = "Bird Detector"
description = "Bird Detector."
examples = ['BIRD.png']
interpretation='default'
enable_queue=True
def combined(img, message):
prediction = predict(img)
response = generate_text(message, history)
if "I have detected" in response:
response = response.replace("I have detected", f"I have detected {prediction['bird']} in the image.")
return response
gr.Interface(fn=combined,inputs=Image(shape=(512, 512)),outputs=Text(),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
|