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---
pipeline_tag: text-generation
tags:
- qwen
- qwen-2
- quantized
- 2-bit
- 3-bit
- 4-bit
- 5-bit
- 6-bit
- 8-bit
- 16-bit
- GGUF
inference: false
model_creator: MaziyarPanahi
model_name: Qwen2-72B-Instruct-v0.1-GGUF
quantized_by: MaziyarPanahi
license: other
license_name: tongyi-qianwen
license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
---
# MaziyarPanahi/Qwen2-72B-Instruct-v0.1-GGUF
The GGUF and quantized models here are based on [MaziyarPanahi/Qwen2-72B-Instruct-v0.1](https://huggingface.co/MaziyarPanahi/Qwen2-72B-Instruct-v0.1) model
## How to download
You can download only the quants you need instead of cloning the entire repository as follows:
```
huggingface-cli download MaziyarPanahi/Qwen2-72B-Instruct-v0.1-GGUF --local-dir . --include '*Q2_K*gguf'
```
## Load GGUF models
You `MUST` follow the prompt template provided by Llama-3:
```sh
./llama.cpp/main -m Meta-Llama-3-70B-Instruct.Q2_K.gguf -p "<|im_start|>user\nJust say 1, 2, 3 hi and NOTHING else\n<|im_end|>\n<|im_start|>assistant\n" -n 1024
```
## Original README
---
# MaziyarPanahi/Qwen2-72B-Instruct-v0.1
This is a fine-tuned version of the `Qwen/Qwen2-72B-Instruct` model. It aims to improve the base model across all benchmarks.
# ⚡ Quantized GGUF
All GGUF models are available here: [MaziyarPanahi/Qwen2-72B-Instruct-v0.1-GGUF](https://huggingface.co/MaziyarPanahi/Qwen2-72B-Instruct-v0.1-GGUF)
# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
| Tasks |Version|Filter|n-shot|Metric|Value | |Stderr|
|--------------|------:|------|-----:|------|-----:|---|-----:|
|truthfulqa_mc2| 2|none | 0|acc |0.6761|± |0.0148|
| Tasks |Version|Filter|n-shot|Metric|Value | |Stderr|
|----------|------:|------|-----:|------|-----:|---|-----:|
|winogrande| 1|none | 5|acc |0.8248|± |0.0107|
| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
|-------------|------:|------|-----:|--------|-----:|---|-----:|
|arc_challenge| 1|none | 25|acc |0.6852|± |0.0136|
| | |none | 25|acc_norm|0.7184|± |0.0131|
|Tasks|Version| Filter |n-shot| Metric |Value | |Stderr|
|-----|------:|----------------|-----:|-----------|-----:|---|-----:|
|gsm8k| 3|strict-match | 5|exact_match|0.8582|± |0.0096|
| | |flexible-extract| 5|exact_match|0.8893|± |0.0086|
# 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/Qwen2-72B-Instruct-v0.1")
pipe(messages)
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/Qwen2-72B-Instruct-v0.1")
model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/Qwen2-72B-Instruct-v0.1")
```
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