2025-04-27 23:59 浙江
模型上新2227、数据集上新270、应用上新167、文章发布10篇
🙋魔搭ModelScope本期社区进展:
📟2227个模型:Bitnet-b1.58-2B-4T、MAGI-1、Dia-1.6B、SkyReels-V2系列等;
📁270个数据集:OpenMathReasoning、xtreme、InternVL-Data等;
🎨167个创新应用:高度逼真的对话声音合成Dia-1.6B、hidream-arena、ChatTests编题等;
📄 10篇内容:
Ollama-Deep-Researcher-本地Mac结合魔搭社区模型搭建网页研究助手
答疑机器人实践:AgentScope多智能体带你玩转多源召回
微软推出bitnet-b1.58-2B-4T:极致的量化,小巧而强大
智源数据新基建系列 Workshop(第1期)来了!从大模型到具身智能,线上线下同步!
ImagePulse图律脉动数据集开源发布:解码GPT-4o级图像生成能力,四大原子数据集+自动生成工具开放
Prot2Chat:融合蛋白质序列与结构的新型问答框架
“一丹一世界”三等奖 | 绮影录 创作分享
“一丹一世界”二等奖 | MAJICFLUS_新浮世 创作分享
"一丹一世界"一等奖 | 曙光_麦橘超然 创作分享
"一丹一世界"二等奖 | TPSZ_二次元卡通梦幻插画风格-童梦拾光_majiuFlux版本 创作分享
Bitnet-b1.58-2B-4T
BitNet-b1.58-2B-4T 是微软开源的一种创新量化模型,采用1.58位的三进制量化方案(权重为+1、0、-1),旨在通过大幅降低计算成本和内存占用,提升大语言模型在端侧等资源受限场景下的应用效率,同时缓解传统量化方法中因精度降低而导致的准确率下降问题。使用transformers进行推理:
环境安装:
!pip install git+https://github.com/shumingma/transformers.git
示例代码
import torch
from modelscope import AutoModelForCausalLM, AutoTokenizer
model_id = "AI-ModelScope/bitnet-b1.58-2B-4T"
# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16
)
# Apply the chat template
messages = [
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "How are you?"},
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
chat_input = tokenizer(prompt, return_tensors="pt").to(model.device)
# Generate response
chat_outputs = model.generate(**chat_input, max_new_tokens=50)
response = tokenizer.decode(chat_outputs[0][chat_input['input_ids'].shape[-1]:], skip_special_tokens=True) # Decode only the response part
print("\nAssistant Response:", response)
更多推理实战教程,详见文章:
微软推出bitnet-b1.58-2B-4T:极致的量化,小巧而强大
MAGI-1
模型地址
docker pull sandai/magi:latest
docker run -it --gpus all --privileged --shm-size=32g --name magi --net=host --ipc=host --ulimit memlock=-1 --ulimit stack=6710886 sandai/magi:latest /bin/bash
# Create a new environment
conda create -n magi python==3.10.12
# Install pytorch
conda install pytorch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 pytorch-cuda=12.4 -c pytorch -c nvidia
# Install other dependencies
pip install -r requirements.txt
# Install ffmpeg
conda install -c conda-forge ffmpeg=4.4
# Install MagiAttention, for more information, please refer to https://github.com/SandAI-org/MagiAttention#
git clone git@github.com:SandAI-org/MagiAttention.git
cd MagiAttention
git submodule update --init --recursive
pip install --no-build-isolation .
模型合集
https://modelscope.cn/collections/SkyReels-V2-f665650130b144model_id=Skywork/SkyReels-V2-DF-14B-540P
# synchronous inference
python3 generate_video_df.py \
--model_id ${model_id} \
--resolution 540P \
--ar_step 0 \
--base_num_frames 97 \
--num_frames 257 \
--overlap_history 17 \
--prompt "A graceful white swan with a curved neck and delicate feathers swimming in a serene lake at dawn, its reflection perfectly mirrored in the still water as mist rises from the surface, with the swan occasionally dipping its head into the water to feed." \
--addnoise_condition 20 \
--offload \
--teacache \
--use_ret_steps \
--teacache_thresh 0.3
model_id=Skywork/SkyReels-V2-DF-14B-540P
# asynchronous inference
python3 generate_video_df.py \
--model_id ${model_id} \
--resolution 540P \
--ar_step 5 \
--causal_block_size 5 \
--base_num_frames 97 \
--num_frames 737 \
--overlap_history 17 \
--prompt "A graceful white swan with a curved neck and delicate feathers swimming in a serene lake at dawn, its reflection perfectly mirrored in the still water as mist rises from the surface, with the swan occasionally dipping its head into the water to feed." \
--addnoise_condition 20 \
--offload
02 数据集推荐
xtreme
XTREME 是一个由谷歌开发的跨语言自然语言推理(XNLI)和多任务基准数据集,旨在评估预训练多语言模型的跨语言泛化能力,涵盖40种语言和九项任务,支持多语言推理和理解的研究与应用。数据集链接:
https://modelscope.cn/datasets/google/xtremeInternVL-Data 是由 OpenGVLab 提供的高质量多模态大语言模型(MLLMs)数据集,专注于图像、文本和视频理解任务,旨在支持相关领域的研究和开发,推动多模态模型在多种任务中的性能提升。
数据集链接:
https://modelscope.cn/datasets/OpenGVLab/InternVL-Data体验直达:
https://modelscope.cn/studios/nari-labs/Dia-1.6B小程序:
Hidream-arena
体验直达:
https://modelscope.cn/studios/WaveSpeed/hidream-arena
小程序:
ChatTests编题
体验直达:
https://modelscope.cn/studios/aomferni/Chattests_2503小程序:
Ollama-Deep-Researcher-本地Mac结合魔搭社区模型搭建网页研究助手
AI赋能大学计划·大模型技术与应用实战学生训练营——华东师范大学站圆满结营
微软推出bitnet-b1.58-2B-4T:极致的量化,小巧而强大
“一丹一世界”二等奖 | MAJICFLUS_新浮世 创作分享
答疑机器人实践:AgentScope多智能体带你玩转多源召回
"一丹一世界"二等奖 | TPSZ_二次元卡通梦幻插画风格-童梦拾光_majiuFlux版本 创作分享
智源数据新基建系列 Workshop(第1期)来了!从大模型到具身智能,线上线下同步!