GGUF
bit-jev
bitnet
structured-decision
pointer-head
cpu-inference
gpu-inference
knowledge-distillation
yelp
custom_code
conversational
Instructions to use jinghao1632/bit-jev-2b-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jinghao1632/bit-jev-2b-distilled with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf jinghao1632/bit-jev-2b-distilled # Run inference directly in the terminal: llama cli -hf jinghao1632/bit-jev-2b-distilled
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jinghao1632/bit-jev-2b-distilled # Run inference directly in the terminal: llama cli -hf jinghao1632/bit-jev-2b-distilled
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf jinghao1632/bit-jev-2b-distilled # Run inference directly in the terminal: ./llama-cli -hf jinghao1632/bit-jev-2b-distilled
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf jinghao1632/bit-jev-2b-distilled # Run inference directly in the terminal: ./build/bin/llama-cli -hf jinghao1632/bit-jev-2b-distilled
Use Docker
docker model run hf.co/jinghao1632/bit-jev-2b-distilled
- LM Studio
- Jan
- Ollama
How to use jinghao1632/bit-jev-2b-distilled with Ollama:
ollama run hf.co/jinghao1632/bit-jev-2b-distilled
- Unsloth Desktop
- Docker Model Runner
How to use jinghao1632/bit-jev-2b-distilled with Docker Model Runner:
docker model run hf.co/jinghao1632/bit-jev-2b-distilled
- Lemonade
How to use jinghao1632/bit-jev-2b-distilled with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jinghao1632/bit-jev-2b-distilled
Run and chat with the model
lemonade run user.bit-jev-2b-distilled-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Add bilingual live demo links to model cards
Browse files- README.en.md +1 -1
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README.en.md
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# bit-jev-2b-distilled
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[中文模型卡](README.md) · [Source repository](https://github.com/Zeaulo/bit-jev) · [pip package](https://pypi.org/project/bit-jev/) · [ModelScope mirror](https://www.modelscope.cn/models/JingHao9616/bit-jev-2b-distilled) · [Live CPU demo](https://
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The bilingual test page lets you edit a customer support scenario and inspect the real model's choice, probabilities, and native compute time. Inference runs in a free ModelScope CPU Space; the free Hugging Face static Space embeds it. First-run download and model loading are excluded from the displayed inference time.
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# bit-jev-2b-distilled
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[中文模型卡](README.md) · [Source repository](https://github.com/Zeaulo/bit-jev) · [pip package](https://pypi.org/project/bit-jev/) · [ModelScope mirror](https://www.modelscope.cn/models/JingHao9616/bit-jev-2b-distilled) · [Live CPU demo](https://jinghao9616-bit-jev-demo.ms.show/) · [Hugging Face bilingual entry](https://huggingface.co/spaces/jinghao1632/bit-jev-demo)
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The bilingual test page lets you edit a customer support scenario and inspect the real model's choice, probabilities, and native compute time. Inference runs in a free ModelScope CPU Space; the free Hugging Face static Space embeds it. First-run download and model loading are excluded from the displayed inference time.
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# bit-jev-2b-distilled
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[English model card](README.en.md) · [源码仓库](https://github.com/Zeaulo/bit-jev) · [pip 安装](https://pypi.org/project/bit-jev/) · [ModelScope 镜像](https://www.modelscope.cn/models/JingHao9616/bit-jev-2b-distilled) · [在线测试](https://
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中英双语测试页可修改客服场景并查看真实模型的选项、概率与原生计算耗时。ModelScope 免费 CPU 空间执行推理;Hugging Face 免费静态 Space 嵌入该空间。首次请求的模型下载与加载不计入页面显示的推理耗时。
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# bit-jev-2b-distilled
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[English model card](README.en.md) · [源码仓库](https://github.com/Zeaulo/bit-jev) · [pip 安装](https://pypi.org/project/bit-jev/) · [ModelScope 镜像](https://www.modelscope.cn/models/JingHao9616/bit-jev-2b-distilled) · [在线测试](https://jinghao9616-bit-jev-demo.ms.show/) · [Hugging Face 双语入口](https://huggingface.co/spaces/jinghao1632/bit-jev-demo)
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中英双语测试页可修改客服场景并查看真实模型的选项、概率与原生计算耗时。ModelScope 免费 CPU 空间执行推理;Hugging Face 免费静态 Space 嵌入该空间。首次请求的模型下载与加载不计入页面显示的推理耗时。
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README.zh-CN.md
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# bit-jev-2b-distilled
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[English model card](README.en.md) · [源码仓库](https://github.com/Zeaulo/bit-jev) · [pip 安装](https://pypi.org/project/bit-jev/) · [ModelScope 镜像](https://www.modelscope.cn/models/JingHao9616/bit-jev-2b-distilled) · [在线测试](https://
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中英双语测试页可修改客服场景并查看真实模型的选项、概率与原生计算耗时。ModelScope 免费 CPU 空间执行推理;Hugging Face 免费静态 Space 嵌入该空间。首次请求的模型下载与加载不计入页面显示的推理耗时。
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# bit-jev-2b-distilled
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[English model card](README.en.md) · [源码仓库](https://github.com/Zeaulo/bit-jev) · [pip 安装](https://pypi.org/project/bit-jev/) · [ModelScope 镜像](https://www.modelscope.cn/models/JingHao9616/bit-jev-2b-distilled) · [在线测试](https://jinghao9616-bit-jev-demo.ms.show/) · [Hugging Face 双语入口](https://huggingface.co/spaces/jinghao1632/bit-jev-demo)
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中英双语测试页可修改客服场景并查看真实模型的选项、概率与原生计算耗时。ModelScope 免费 CPU 空间执行推理;Hugging Face 免费静态 Space 嵌入该空间。首次请求的模型下载与加载不计入页面显示的推理耗时。
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