Spaces:
Runtime error
Runtime error
File size: 1,337 Bytes
bc35043 |
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 |
import torch
from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig
import gradio as gr
import warnings
import os
# Remove command-line arguments parsing and use hardcoded defaults for simplicity in Spaces
MODEL_PATH = "/model/13B_hf"
LORA_PATH = "checkpoint-3000"
USE_TYPEWRITER = 1
USE_LOCAL = 1
tokenizer = LlamaTokenizer.from_pretrained(MODEL_PATH)
LOAD_8BIT = True
BASE_MODEL = MODEL_PATH
LORA_WEIGHTS = LORA_PATH
lora_bin_path = os.path.join(LORA_PATH, "adapter_model.bin")
if not os.path.exists(lora_bin_path) and USE_LOCAL:
# ... [rest of the path fixing logic]
# ... [rest of the device and model loading logic]
def generate_prompt(instruction, input=None):
# ... [rest of the generate_prompt function]
def evaluate(
input,
temperature=0.1,
top_p=0.75,
top_k=40,
num_beams=4,
max_new_tokens=128,
min_new_tokens=1,
repetition_penalty=2.0,
**kwargs,
):
# ... [rest of the evaluate function]
gr.Interface(
fn=evaluate,
inputs=[
gr.components.Textbox(lines=2, label="Input", placeholder="Tell me about alpacas."),
# ... [rest of the inputs]
],
outputs=[
gr.inputs.Textbox(lines=25, label="Output"),
],
title="Chinese-Vicuna 中文小羊驼",
description="Chatlaw app trained on HK law data",
).launch()
|