Text Generation
Transformers
English
qwen2
code-generation
python
fine-tuning
Qwen
tools
agent-framework
multi-agent
conversational
Eval Results (legacy)
Instructions to use my-ai-stack/Stack-2-9-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use my-ai-stack/Stack-2-9-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="my-ai-stack/Stack-2-9-finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("my-ai-stack/Stack-2-9-finetuned") model = AutoModelForCausalLM.from_pretrained("my-ai-stack/Stack-2-9-finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use my-ai-stack/Stack-2-9-finetuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "my-ai-stack/Stack-2-9-finetuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
- SGLang
How to use my-ai-stack/Stack-2-9-finetuned 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 "my-ai-stack/Stack-2-9-finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "my-ai-stack/Stack-2-9-finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use my-ai-stack/Stack-2-9-finetuned with Docker Model Runner:
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
File size: 3,300 Bytes
b6ae7b8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 | #!/bin/bash
#
# Stack 2.9 Deployment Validation Script
# Verifies that all required files are present and properly configured
#
set -e
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
NC='\033[0m'
ERRORS=0
WARNINGS=0
echo "Validating Stack 2.9 deployment files..."
echo ""
# Check required files
echo "Checking core files..."
REQUIRED_FILES=(
"Dockerfile"
"docker-compose.yaml"
"deploy.sh"
"app.py"
"config.yaml"
"runpod-template.json"
"vastai-template.json"
"README.md"
)
for file in "${REQUIRED_FILES[@]}"; do
if [ -f "$SCRIPT_DIR/$file" ]; then
echo -e " ${GREEN}β${NC} $file"
else
echo -e " ${RED}β${NC} $file (missing)"
((ERRORS++))
fi
done
echo ""
echo "Checking Kubernetes manifests..."
K8S_FILES=(
"kubernetes/deployment.yaml"
"kubernetes/service.yaml"
"kubernetes/pvc.yaml"
"kubernetes/hpa.yaml"
"kubernetes/secrets.yaml"
)
for file in "${K8S_FILES[@]}"; do
if [ -f "$SCRIPT_DIR/$file" ]; then
echo -e " ${GREEN}β${NC} $file"
else
echo -e " ${YELLOW}β ${NC} $file (missing)"
((WARNINGS++))
fi
done
echo ""
echo "Checking permissions..."
if [ -x "$SCRIPT_DIR/deploy.sh" ]; then
echo -e " ${GREEN}β${NC} deploy.sh is executable"
else
echo -e " ${YELLOW}β ${NC} deploy.sh is not executable (run: chmod +x deploy.sh)"
((WARNINGS++))
fi
echo ""
echo "Checking Docker..."
if command -v docker &> /dev/null; then
echo -e " ${GREEN}β${NC} Docker ($(docker --version | head -n1))"
else
echo -e " ${YELLOW}β ${NC} Docker not found (required for local deployment)"
((WARNINGS++))
fi
if command -v docker-compose &> /dev/null; then
echo -e " ${GREEN}β${NC} Docker Compose ($(docker-compose --version | head -n1))"
else
echo -e " ${YELLOW}β ${NC} Docker Compose not found (required for local deployment)"
((WARNINGS++))
fi
echo ""
echo "Checking NVIDIA GPU..."
if command -v nvidia-smi &> /dev/null; then
echo -e " ${GREEN}β${NC} NVIDIA GPU detected"
nvidia-smi --query-gpu=name --format=csv,noheader | head -1
else
echo -e " ${YELLOW}β ${NC} No NVIDIA GPU detected (CPU-only mode will be slower)"
((WARNINGS++))
fi
echo ""
echo "Checking Kubernetes..."
if command -v kubectl &> /dev/null; then
echo -e " ${GREEN}β${NC} kubectl available"
if kubectl cluster-info &> /dev/null; then
echo -e " ${GREEN}β${NC} Connected to cluster"
else
echo -e " ${YELLOW}β ${NC} kubectl not configured"
fi
else
echo -e " ${YELLOW}β ${NC} kubectl not found (required for K8s deployment)"
fi
echo ""
echo "ββββββββββββββββββββββββββββββββββββββββββββββββββββ"
if [ $ERRORS -eq 0 ] && [ $WARNINGS -eq 0 ]; then
echo -e "${GREEN}All checks passed! β${NC}"
echo "You can deploy with: ./deploy.sh local"
exit 0
elif [ $ERRORS -eq 0 ]; then
echo -e "${YELLOW}Validation complete with $WARNINGS warning(s)${NC}"
echo "Fix warnings before deployment, or proceed with caution."
exit 0
else
echo -e "${RED}Validation failed with $ERRORS error(s)${NC}"
exit 1
fi
|