Instructions to use Weyaxi/SlimOpenOrca-Mistral-7B-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Weyaxi/SlimOpenOrca-Mistral-7B-v2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Weyaxi/SlimOpenOrca-Mistral-7B-v2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Weyaxi/SlimOpenOrca-Mistral-7B-v2")
model = AutoModelForCausalLM.from_pretrained("Weyaxi/SlimOpenOrca-Mistral-7B-v2")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Weyaxi/SlimOpenOrca-Mistral-7B-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Weyaxi/SlimOpenOrca-Mistral-7B-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Weyaxi/SlimOpenOrca-Mistral-7B-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Weyaxi/SlimOpenOrca-Mistral-7B-v2

SGLang

How to use Weyaxi/SlimOpenOrca-Mistral-7B-v2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Weyaxi/SlimOpenOrca-Mistral-7B-v2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Weyaxi/SlimOpenOrca-Mistral-7B-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Weyaxi/SlimOpenOrca-Mistral-7B-v2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Weyaxi/SlimOpenOrca-Mistral-7B-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Weyaxi/SlimOpenOrca-Mistral-7B-v2 with Docker Model Runner:
```
docker model run hf.co/Weyaxi/SlimOpenOrca-Mistral-7B-v2
```

Merge of Open-Orca/Mistral-7B-SlimOrca and Open-Orca/Mistral-7B-OpenOrca using ties merge.

Weights

Open-Orca/Mistral-7B-SlimOrca: 0.6
Open-Orca/Mistral-7B-OpenOrca: 0.4

Density

Open-Orca/Mistral-7B-SlimOrca: 0.5
Open-Orca/Mistral-7B-OpenOrca: 0.5

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	52.96
ARC (25-shot)	62.88
HellaSwag (10-shot)	83.41
MMLU (5-shot)	62.05
TruthfulQA (0-shot)	56.65
Winogrande (5-shot)	77.58
GSM8K (5-shot)	18.95
DROP (3-shot)	9.19

Downloads last month: 53

Safetensors

Model size

7B params

Tensor type

F32

BF16

Collection including Weyaxi/SlimOpenOrca-Mistral-7B-v2

Merge models

Collection

Merge models created with mergekit • 19 items • Updated Dec 3, 2025 • 3