Instructions to use 54093LEE/Qwen2.5-7B-JavaScript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 54093LEE/Qwen2.5-7B-JavaScript with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("54093LEE/Qwen2.5-7B-JavaScript", dtype="auto")

llama-cpp-python

How to use 54093LEE/Qwen2.5-7B-JavaScript with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="54093LEE/Qwen2.5-7B-JavaScript",
	filename="Qwen2.5-7B-JavaScript.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use 54093LEE/Qwen2.5-7B-JavaScript with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf 54093LEE/Qwen2.5-7B-JavaScript
# Run inference directly in the terminal:
llama-cli -hf 54093LEE/Qwen2.5-7B-JavaScript

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf 54093LEE/Qwen2.5-7B-JavaScript
# Run inference directly in the terminal:
llama-cli -hf 54093LEE/Qwen2.5-7B-JavaScript

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 54093LEE/Qwen2.5-7B-JavaScript
# Run inference directly in the terminal:
./llama-cli -hf 54093LEE/Qwen2.5-7B-JavaScript

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 54093LEE/Qwen2.5-7B-JavaScript
# Run inference directly in the terminal:
./build/bin/llama-cli -hf 54093LEE/Qwen2.5-7B-JavaScript

Use Docker

docker model run hf.co/54093LEE/Qwen2.5-7B-JavaScript

LM Studio
Jan
Ollama
How to use 54093LEE/Qwen2.5-7B-JavaScript with Ollama:
```
ollama run hf.co/54093LEE/Qwen2.5-7B-JavaScript
```

Unsloth Studio new

How to use 54093LEE/Qwen2.5-7B-JavaScript with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for 54093LEE/Qwen2.5-7B-JavaScript to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for 54093LEE/Qwen2.5-7B-JavaScript to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for 54093LEE/Qwen2.5-7B-JavaScript to start chatting

Docker Model Runner
How to use 54093LEE/Qwen2.5-7B-JavaScript with Docker Model Runner:
```
docker model run hf.co/54093LEE/Qwen2.5-7B-JavaScript
```

Lemonade

How to use 54093LEE/Qwen2.5-7B-JavaScript with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull 54093LEE/Qwen2.5-7B-JavaScript

Run and chat with the model

lemonade run user.Qwen2.5-7B-JavaScript-{{QUANT_TAG}}

List all available models

lemonade list

Worse answers then original Qwen2.5-7B Coder

by d9k - opened May 26, 2025

Discussion

d9k

May 26, 2025

Question

What are the best React UI frameworks?

Qwen2.5-7B-JavaScript

As an AI language model, I don't have personal preferences or experiences. However, there are some popular and widely used React UI frameworks that developers often recommend:

Material-UI: It provides a set of ready-to-use components that follow Google's Material Design guidelines.
Ant Design: It offers a wide range of customizable UI components for building enterprise-class applications.
Bootstrap-React: It is based on the popular Bootstrap framework, providing pre-built React components and styles.
Each of these frameworks has its strengths and weaknesses, so it's important to evaluate them based on your specific project requirements before making a decision.

Original Qwen2.5-7B Coder

React has several popular and powerful UI frameworks that can help you build user interfaces quickly and efficiently. Here are some of the best React UI frameworks:

Material-UI: This framework provides a comprehensive set of pre-built, accessible Material Design components for building modern web applications.

Ant Design (antd): Developed by Alibaba Cloud, this framework offers a wide range of components that follow Ant Design's design language, making it highly customizable and consistent with other Alibaba products.

Semantic UI React: Based on the popular Semantic UI CSS library, this framework provides a set of components that are intuitive to use and easy to style.

Chakra UI: This is a free and open-source UI component library built on top of React and Tailwind CSS. It's designed to be simple, flexible, and accessible.

Reflexbox: This is a CSS-in-JS utility library that helps you create responsive layouts easily without writing any CSS.

Styled Components: While not technically a framework, Styled Components allows you to write CSS-in-JS which can help in creating unique styles for your components.

Emotion: Similar to Styled Components, Emotion is another popular choice for writing CSS-in-JS and can be used with React to create dynamic styles.

Bootstrap Material Design: A collection of React components that use Bootstrap's CSS framework along with the Google's Material design language.

Bulma React: A set of React components based on the Bulma CSS library, which is a modern front-end framework for building responsive web interfaces.

Downshift: A simple React state management and accessibility library to help you create custom dropdowns, menus, and comboboxes.

Each of these frameworks has its own strengths and use cases. The choice of which one to use depends on your specific needs, such as design preferences, project complexity, and team familiarity

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