Model: Berkelium-ai/BerkeliumGPT-Coder-3b Source: Original Platform
language, license, pipeline_tag, library_name, tags, datasets, base_model
| language | license | pipeline_tag | library_name | tags | datasets | base_model | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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apache-2.0 | text-generation | mlx |
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🚀 BerkeliumGPT-Coder-3B
Production-Grade Agentic Coding Model
Built for software engineering, code generation, debugging, repository understanding, and autonomous coding workflows.
Quick Start
Transformers
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "berkelium-ai/BerkeliumGPT-Coder-3B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
device_map="auto",
torch_dtype="auto"
)
MLX
mlx_lm.generate \
--model berkelium-ai/BerkeliumGPT-Coder-3B \
--prompt "Build a FastAPI backend."
Docker Model Runner
docker model pull hf.co/berkelium-ai/BerkeliumGPT-Coder-3B
docker model run hf.co/berkelium-ai/BerkeliumGPT-Coder-3B
Ollama (GGUF Release)
ollama run berkeliumgpt-coder
Model Details
| Property | Value |
|---|---|
| Model Name | BerkeliumGPT-Coder-3B |
| Base Model | Qwen2.5-3B-Instruct |
| Parameters | 3 Billion |
| Architecture | Transformer Decoder |
| Domain | Software Engineering |
| Context Length | Base Model Configuration |
| License | Apache-2.0 |
Capabilities
- Code Generation
- Agentic Coding
- Repository Analysis
- Bug Detection
- Refactoring
- Test Generation
- Documentation Writing
- API Development
- DevOps Automation
Supported Languages
- Python
- JavaScript
- TypeScript
- Go
- Rust
- Java
- C++
- C#
- SQL
- Bash
- HTML
- CSS
Example Prompt
User
Build a FastAPI application with JWT authentication and PostgreSQL.
Assistant
Generates:
- Backend API
- Database models
- Authentication system
- Docker configuration
- Unit tests
Intended Use
BerkeliumGPT-Coder-3B is designed for:
- AI Coding Assistants
- Software Engineering Agents
- Developer Copilots
- Research
- Local Inference
- Autonomous Development Workflows
Limitations
- Generated code should be reviewed before production deployment.
- Security auditing is recommended.
- Human validation remains essential.
License
Apache-2.0
Description
Languages
Jinja
100%
