Downloads · 30 days
18
5% of all-time downloads
qwen-1.7b-coder
XformAI-india/qwen-1.7b-coder
qwen-1.7b-coder is a machine learning model from XformAI-india. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Model: XformAI-india/qwen-1.7b-coder Base Model: Qwen/Qwen3-1.7B Architecture: Transformer decoder (GPT-style) Size: 1.7 Billion Parameters Fine-Tuned By: XformAI Release Date: May 2025 License: MIT
All-time downloads
346
Public
Parameters
1.7B
3.5 GB on disk
Likes
3
Public
Repo makeup
Click a slice to open those files.
.safetensors3.4 GB · 100%
At a glance
- License
- mit
- Model type
- qwen3
- Access
- Public
- Created
- May 2, 2025
- Updated
- May 2, 2025
- SHA
- 7b326e36
Base models
Model card
From the Hugging Face model README
💻 Qwen-1.7B Coder – XformAI Fine-Tuned
Model: XformAI-india/qwen-1.7b-coder
Base Model: Qwen/Qwen3-1.7B
Architecture: Transformer decoder (GPT-style)
Size: 1.7 Billion Parameters
Fine-Tuned By: XformAI
Release Date: May 2025
License: MIT
🚀 Overview
qwen-1.7b-coder is a purpose-built code generation model, fine-tuned from Qwen3 1.7B by XformAI to deliver highly usable Python, JS, and Bash snippets with low-latency inference.
Designed to help:
- 🧑💻 Developers
- 🧠 AI agents
- ⚙️ Backend toolchains
Generate and complete code reliably — both in IDEs and on edge devices.
🧠 Training Highlights
| Aspect | Value |
|---|---|
| Fine-Tuning Type | Instruction-tuned on code corpus |
| Target Domains | Python, Bash, HTML, JavaScript |
| Style | Docstring-to-code, prompt-to-app |
| Tuning Technique | LoRA (8-bit) + PEFT |
| Framework | 🤗 Transformers |
| Precision | bfloat16 |
| Epochs | 3 |
| Max Tokens | 2048 |
🔧 Use Cases
- VSCode-like autocomplete agents
- Shell command assistants
- Backend logic & API template generation
- Code-aware chatbots
- On-device copilots
✍️ Example Prompt + Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("XformAI-india/qwen-1.7b-coder")
tokenizer = AutoTokenizer.from_pretrained("XformAI-india/qwen-1.7b-coder")
prompt = "Write a Python script that takes a directory path and prints all .txt file names inside it."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
- Type
- qwen3
- License
- mit
- Created
- May 2, 2025
- Updated
- May 2, 2025