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XformAI-india/
qwen-1.7b-coder

Name: qwen-1.7b-coder
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💻 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

python

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))