d0dc94e36d
新功能: - 创建AI聊天助手组件（AIChatWidget） - 支持文字+图片多模态对话 - 集成Gemini AI API - 支持图片编辑和内容生成 - 实时对话历史管理 - 优雅的UI设计，支持黑夜模式 技术实现: - 后端API代理Gemini API（/api/ai-chat） - 支持最多5张图片上传 - 流式响应处理 - 对话历史管理 - Base64图片处理 配置: - 在.env中添加Gemini API配置 - GEMINI_API_KEY - GEMINI_API_BASE_URL - GEMINI_MODEL 替换原弹幕功能，提供更强大的AI助手体验！
29 lines
970 B
Python
Executable File
29 lines
970 B
Python
Executable File
import os
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from typing import Tuple
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try:
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import torch
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from transformers import AutoModel, AutoTokenizer
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from transformers.tokenization_utils import PreTrainedTokenizer
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except ImportError:
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raise ImportError("Please make sure to install torch and transformers: "
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"\n pip install torch~=1.13 \n pip install transformers~=4.30.2")
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def get_bottom_model(model_id: str) -> Tuple["PreTrainedTokenizer", "torch.nn.Embedding"]:
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"""
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Load the specified pre-trained model from huggingface and save the embedding model and tokenizer
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:param model_id: id of pre-trained model
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:return None
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"""
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model = AutoModel.from_pretrained(model_id, trust_remote_code=True)
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# Search the embedding layer
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for name, module in model.named_modules():
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if isinstance(module, torch.nn.Embedding):
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break
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tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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return tokenizer, module
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