kadirnar/combined-turkish-datasets-v5
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How to use Kasimyildirim/Qwen2-turkish-comnibed-v5-lora with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="Kasimyildirim/Qwen2-turkish-comnibed-v5-lora") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Kasimyildirim/Qwen2-turkish-comnibed-v5-lora", dtype="auto")How to use Kasimyildirim/Qwen2-turkish-comnibed-v5-lora with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Kasimyildirim/Qwen2-turkish-comnibed-v5-lora"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Kasimyildirim/Qwen2-turkish-comnibed-v5-lora",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/Kasimyildirim/Qwen2-turkish-comnibed-v5-lora
How to use Kasimyildirim/Qwen2-turkish-comnibed-v5-lora with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "Kasimyildirim/Qwen2-turkish-comnibed-v5-lora" \
--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": "Kasimyildirim/Qwen2-turkish-comnibed-v5-lora",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "Kasimyildirim/Qwen2-turkish-comnibed-v5-lora" \
--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": "Kasimyildirim/Qwen2-turkish-comnibed-v5-lora",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use Kasimyildirim/Qwen2-turkish-comnibed-v5-lora with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Kasimyildirim/Qwen2-turkish-comnibed-v5-lora to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Kasimyildirim/Qwen2-turkish-comnibed-v5-lora to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Kasimyildirim/Qwen2-turkish-comnibed-v5-lora to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="Kasimyildirim/Qwen2-turkish-comnibed-v5-lora",
max_seq_length=2048,
)How to use Kasimyildirim/Qwen2-turkish-comnibed-v5-lora with Docker Model Runner:
docker model run hf.co/Kasimyildirim/Qwen2-turkish-comnibed-v5-lora
This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
Base model
Qwen/Qwen2.5-VL-7B-Instruct