---
language:
- en
- code
language_bcp47:
- en
- javascript
license: apache-2.0
tags:
- text-generation
- code
- javascript
- coding-assistant
- fine-tuning
- merged
- unsloth
- gpt-oss
- vllm
base_model: openai/gpt-oss-20b
library_name: transformers
pipeline_tag: text-generation
model-index:
- name: gpt-oss-coder-v0.1-javascript
  results: []
---

# gpt-oss-coder-v0.1-javascript

A **language-specialized coding model for JavaScript**, fine-tuned from OpenAI's open-weight **gpt-oss** base with **very small, curated JS data** using **Unsloth**.  
This release prioritizes **practical code generation quality** over benchmark scores. The model weights have been **merged** and are ready for deployment.

> **Status**: Experimental preview (`v0.1-javascript`)  
> **Focus**: JS coding tasks (function-level completion, small refactors, idiomatic patterns)  
> **Testing**: Currently undergoing validation with vLLM deployment  
> **Note**: This repository contains merged weights, not LoRA adapters

---

## Model Details

- **Model type**: Causal LM (decoder-only), JS-specialized fine-tune  
- **Base model**: `openai/gpt-oss-20b` (open-weight, Apache-2.0)  
- **Fine-tuning**: LoRA via **Unsloth**, weights merged post-training  
- **License**: Apache-2.0 (derivative weights released under Apache-2.0)  
- **Author / Maintainer**: `hokar3361`  
- **Intended Languages**: JavaScript (ES6+); English prompts recommended
- **Weight Format**: Merged (full model weights)

---

## Intended Use & Limitations

### Intended Use
- Code completion and synthesis for **JavaScript**
- Small refactors, idiomatic rewrites, test scaffolding, JSDoc/docstrings
- Snippet-level reasoning and bug fixes

### Out of Scope / Limitations
- Not a substitute for static analysis, linters, or security review
- May hallucinate APIs or types; verify before production use
- Trained on **small** domain data → expect gaps on rare frameworks or edge APIs

---

## Quickstart

### 1. Start vLLM Server

Since this repository contains **merged weights**, you can run directly with vLLM:

```bash
vllm serve hokar3361/gpt-oss-coderjs-v0.1 \
  --async-scheduling \
  --max-model-len 16000 \
  --gpu-memory-utilization 0.90
```

**Recommended**: Use `--max-model-len 16000` for optimal context handling.

### 2. Client Usage (Recommended)

Use the **OpenAI Python client** to call the vLLM server:

```python
from openai import OpenAI

# Point to your vLLM server
client = OpenAI(
    base_url="http://localhost:8000/v1",
    api_key="dummy"  # vLLM doesn't require auth by default
)

response = client.completions.create(
    model="hokar3361/gpt-oss-coderjs-v0.1",
    prompt="// JavaScript function to validate email addresses\nfunction validateEmail(email) {",
    # DO NOT specify temperature or max_tokens - let the model use defaults
)

print(response.choices[0].text)
```

**Important**: 
- **Do not specify** `temperature` or `max_tokens` parameters - the model performs best with default values
- Use the OpenAI Python client for best compatibility and stability

---

## Testing & Validation

### Current Status
The model is currently being validated using vLLM deployment. Initial testing shows **improved performance** compared to pre-fine-tuning baseline.

### Evaluation Methodology
- **Test Set**: 50 programming questions from GitHub and Stack Overflow
- **Judges**: GPT-5 and Claude Opus for response quality assessment
- **Preliminary Results**: The fine-tuned model demonstrates better code generation quality on JavaScript-specific tasks compared to the base model
- **Note**: Full benchmark validation is still in progress

---

## Acknowledgements

This work was made possible thanks to the open-weight release of **gpt-oss** by OpenAI, which provided a strong foundation under the Apache-2.0 license.

Special thanks to the open-source community around **Unsloth** for enabling memory-efficient and rapid LoRA fine-tuning on limited hardware.

We also thank the **Hugging Face** and **vLLM** ecosystems for lowering the barrier to experimentation.

---

## Disclaimer & Experimental Status

This model (`v0.1-javascript`) is highly experimental:

- **Small data**: Fine-tuned on a very small JavaScript-focused dataset, mainly to validate the workflow and feasibility of language specialization.

- **Not production-ready**: The model may generate incomplete, insecure, or non-idiomatic code; do not rely on it for production use without careful review.

- **Testing in progress**: While initial results from GPT-5 and Opus evaluation show improvements, comprehensive benchmarking is ongoing.

- **Early stage**: This is only an initial exploration; future versions with larger, more diverse training corpora are expected to improve stability and coverage.

We share this release to contribute to the community and gather early feedback.  
**Use responsibly, validate outputs, and treat this as a proof-of-concept.**