metadata
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-v0.2
datasets:
- nvidia/HelpSteer2
- teknium/OpenHermes-2.5
- microsoft/orca-math-word-problems-200k
- Open-Orca/SlimOrca
![Qwen2 fine-tune](/MaziyarPanahi/calme-2.2-qwen2-7b/resolve/main/qwen2-fine-tunes-maziyar-panahi.webp)
MaziyarPanahi/Qwen2-7B-Instruct-v0.2
This is a fine-tuned version of the Qwen/Qwen2-7B
model. It aims to improve the base model across all benchmarks.
β‘ Quantized GGUF
All GGUF models are available here: MaziyarPanahi/Qwen2-7B-Instruct-v0.2-GGUF
π Open LLM Leaderboard Evaluation Results
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
# 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-v0.2")
pipe(messages)
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/Qwen2-7B-Instruct-v0.2")
model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/Qwen2-7B-Instruct-v0.2")