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Model: dheeyantra/dhee-nxtgen-qwen3-bengali-v2
Source: Original Platform

README.md

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+---
+language: bn
+license: apache-2.0
+tags:
+  - causal-lm
+  - assistant
+  - reasoning
+  - bengali
+model_name: dhee-nxtgen-qwen3-bengali-v2
+library_name: transformers
+---
+
+# Dhee-NxtGen-Qwen3-Bengali-v2
+
+## Model Description
+**Dhee-NxtGen-Qwen3-Bengali-v2** is a large language model designed for natural and fluent Bengali (Bangla) understanding and generation.  
+Built upon the **Qwen3** architecture, this model is optimized for **assistant-style dialogue**, **function-calling tasks**, and **reasoning-oriented responses**.
+
+It is part of DheeYantra’s multilingual initiative in collaboration with **NxtGen Cloud Technologies Private Limited**, focusing on building domain-adapted Indic LLMs.
+
+## Key Features
+- Fluent, context-aware Bengali text generation  
+- Fine-tuned for assistant-style interactions and reasoning tasks  
+- Handles open-domain question answering, summarization, and dialogue  
+- Fully compatible with 🤗 Hugging Face Transformers  
+- Optimized for VLLM serving for high-performance inference  
+
+## Example Usage
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "dheeyantra/dhee-nxtgen-qwen3-bengali-v2"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
+
+# Qwen3-compatible formatted prompt
+prompt = """<|im_start|>system
+You are a helpful assistant.<|im_end|>
+<|im_start|>user
+তুমি কি আমার জন্য একটি অ্যাপয়েন্টমেন্ট নির্ধারণ করতে পারবে?<|im_end|>
+<|im_start|>assistant
+"""
+
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=150)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Intended Uses & Limitations
+### Intended Uses
+- Bengali conversational chatbots and assistants  
+- Function-calling and structured response generation  
+- Story generation and summarization in Bengali  
+- Natural dialogue systems for Indic AI applications  
+
+### Limitations
+- May generate inaccurate or biased responses in rare cases  
+- Performance can vary on out-of-domain or code-mixed inputs  
+- Primarily optimized for Bengali; other languages may produce less fluent results  
+
+## VLLM / High-Performance Serving Requirements
+For high-throughput serving with **vLLM**, ensure the following environment:
+
+- GPU with compute capability ≥ 8.0 (e.g., NVIDIA A100)  
+- PyTorch 2.1+ and CUDA toolkit installed  
+- For V100 GPUs (sm70), vLLM GPU inference is not supported; CPU fallback is possible but slower.  
+
+Install dependencies:
+```bash
+pip install torch transformers vllm sentencepiece
+```
+
+Run vLLM server:
+```bash
+vllm serve   --model dheeyantra/dhee-nxtgen-qwen3-bengali-v2   --host 0.0.0.0   --port 8000
+```
+
+## License
+Released under the **Apache 2.0 License**.
+
+---
+*Developed by DheeYantra in collaboration with NxtGen Cloud Technologies Pvt. Ltd.*