🚀 iq-code-evmind-v1-granite-8b-instruct模型项目

本项目提供了一个基于iq-code-evmind-v1-granite-8b-instruct模型的代码示例，可用于生成智能合约相关内容，解决了在特定场景下智能合约生成的需求，为开发者提供了便利。

🚀 快速开始

以下是使用iq-code-evmind-v1-granite-8b-instruct模型生成智能合约内容的示例代码：

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda"
model_path = "braindao/iq-code-evmind-v1-granite-8b-instruct"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path, device_map=device)
model.eval()

chat = [
    {
        "role": "user",
        "content": "Create a smart contract to serve as a centralized review system called ReviewHub. This contract should allow users to submit and manage reviews for various products or services, rate them on a scale of 1 to 5, and provide detailed comments. It should include functionalities for assigning unique identifiers to products or services, storing and retrieving reviews, allowing users to edit or delete their reviews, calculating average ratings, and enabling an administrator to moderate content. The contract must incorporate robust security measures to ensure review integrity and prevent spam or malicious activity."
    },
]

chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
input_tokens = tokenizer(chat, return_tensors="pt")
for i in input_tokens:
    input_tokens[i] = input_tokens[i].to(device)
output = model.generate(**input_tokens, max_new_tokens=4096)
output = tokenizer.batch_decode(output)
for i in output:
    print(i)

💻 使用示例

基础用法

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda"
model_path = "braindao/iq-code-evmind-v1-granite-8b-instruct"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path, device_map=device)
model.eval()

chat = [
    {
        "role": "user",
        "content": "Create a smart contract to serve as a centralized review system called ReviewHub. This contract should allow users to submit and manage reviews for various products or services, rate them on a scale of 1 to 5, and provide detailed comments. It should include functionalities for assigning unique identifiers to products or services, storing and retrieving reviews, allowing users to edit or delete their reviews, calculating average ratings, and enabling an administrator to moderate content. The contract must incorporate robust security measures to ensure review integrity and prevent spam or malicious activity."
    },
]

chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
input_tokens = tokenizer(chat, return_tensors="pt")
for i in input_tokens:
    input_tokens[i] = input_tokens[i].to(device)
output = model.generate(**input_tokens, max_new_tokens=4096)
output = tokenizer.batch_decode(output)
for i in output:
    print(i)

高级用法

# 可根据实际需求修改输入的聊天内容，以生成不同的智能合约相关内容。
# 例如，可以修改用户的提问，让模型生成不同功能的智能合约。
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda"
model_path = "braindao/iq-code-evmind-v1-granite-8b-instruct"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path, device_map=device)
model.eval()

# 修改聊天内容
chat = [
    {
        "role": "user",
        "content": "Create a different smart contract for a decentralized voting system. This contract should allow users to vote on proposals, count votes, and ensure the fairness and transparency of the voting process."
    },
]

chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
input_tokens = tokenizer(chat, return_tensors="pt")
for i in input_tokens:
    input_tokens[i] = input_tokens[i].to(device)
output = model.generate(**input_tokens, max_new_tokens=4096)
output = tokenizer.batch_decode(output)
for i in output:
    print(i)

📄 许可证

本项目使用的许可证为Apache-2.0。

📦 相关信息