README.md

---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- chat
- qwen
- qwen2
- finetune
- chatml
- OpenHermes-2.5
- HelpSteer2
- Orca
- SlimOrca
library_name: transformers
inference: false
model_creator: MaziyarPanahi
quantized_by: MaziyarPanahi
base_model: Qwen/Qwen2-7B
model_name: Qwen2-7B-Instruct-v0.8
datasets:
- nvidia/HelpSteer2
- teknium/OpenHermes-2.5
- microsoft/orca-math-word-problems-200k
- Open-Orca/SlimOrca
---

<img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>

# MaziyarPanahi/Qwen2-7B-Instruct-v0.8

This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.

# ⚡ Quantized GGUF

All GGUF models are available here: [MaziyarPanahi/Qwen2-7B-Instruct-v0.8-GGUF](https://huggingface.co/MaziyarPanahi/Qwen2-7B-Instruct-v0.8-GGUF)

# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)

coming soon!


# Prompt Template

This model uses `ChatML` prompt template:

```
<|im_start|>system
{System}
<|im_end|>
<|im_start|>user
{User}
<|im_end|>
<|im_start|>assistant
{Assistant}
````

# How to use


```python

# Use a pipeline as a high-level helper

from transformers import pipeline

messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe = pipeline("text-generation", model="MaziyarPanahi/Qwen2-7B-Instruct-v0.8")
pipe(messages)


# Load model directly

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/Qwen2-7B-Instruct-v0.8")
model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/Qwen2-7B-Instruct-v0.8")
```