metadata
language:
- en
- vi
pretty_name: Chatbot IELTS Assistant v2
license: apache-2.0
tags:
- qwen3
- chatbot
- conversational
- ielts
- education
- text-generation
base_model:
- Qwen/Qwen3-4B-Instruct-2507
📘 Chatbot IELTS Assistant v2
Chatbot IELTS Assistant v2 is a fine-tuned conversational language model built on Qwen3-4B-2507, designed to assist learners preparing for the IELTS exam.
It provides natural dialogue responses and helpful explanations for Speaking, Writing, Reading, Listening, vocabulary, and grammar.
📌 Model Summary
| Attribute | Value |
|---|---|
| Model type | Conversational LLM |
| Base model | Qwen3-4B-2507 |
| Training | Fine-tuned for IELTS-related dialogue |
| Languages | English, Vietnamese |
| License | Apache-2.0 |
| Intended use | IELTS learning assistant |
🎯 Intended Use Cases
This model is suitable for:
- IELTS Speaking practice
- IELTS Writing task explanations
- Vocabulary & grammar guidance
- English learning conversation
- General educational Q&A
NOT recommended for:
- Legal, medical, financial advice
- High-risk decision making
- Producing official IELTS scores
🚀 How to Use
Python (Transformers)
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "Zkare/Chatbot_Ielts_Assistant_v2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
prompt = "Help me practice IELTS Speaking Part 2."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=180)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))