---
license: apache-2.0
base_model: unsloth/Qwen3-30B-A3B-Instruct-2507
tags:
  - qwen3
  - chat
  - instruct
---

# OpenPipe/Qwen3-30B-A3B-Instruct-2507

This is a copy of [unsloth/Qwen3-30B-A3B-Instruct-2507](https://huggingface.co/unsloth/Qwen3-30B-A3B-Instruct-2507) with a **fixed chat template** for SFT training.

## Changes from the original

The only change is the chat template. The original Qwen3 chat template adds `<think></think>` tags **inconsistently** - only to the last assistant message in a conversation, not to earlier assistant messages in the history.

This causes issues during SFT training because:
- Historical assistant messages: `<|im_start|>assistant\nHi there!<|im_end|>`
- Target assistant message: `<|im_start|>assistant\n<think>\n\n</think>\n\nI am well!<|im_end|>`

The model learns an inconsistent pattern, leading to degraded outputs.

## Fixed template

This model uses a **consistent** chat template that adds `<think>\n\n</think>\n\n` to ALL assistant messages:

```
{{- '<|im_start|>assistant\n<think>\n\n</think>\n\n' + content }}
```

This ensures the model learns a single, consistent pattern during training.

## Usage

Use this model as your base model for SFT training with Qwen3-30B-A3B when you need consistent chat formatting.

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("OpenPipe/Qwen3-30B-A3B-Instruct-2507")
model = AutoModelForCausalLM.from_pretrained("OpenPipe/Qwen3-30B-A3B-Instruct-2507")
```

## Model Details

- **Base Model**: [unsloth/Qwen3-30B-A3B-Instruct-2507](https://huggingface.co/unsloth/Qwen3-30B-A3B-Instruct-2507)
- **Parameters**: 30B (3B active with MoE)
- **License**: Apache 2.0