Instructions to use Derinhelm/Syntax_Qwen3_14B_Base_gsd_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Derinhelm/Syntax_Qwen3_14B_Base_gsd_7 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/models/Qwen3-14B-Base") model = PeftModel.from_pretrained(base_model, "Derinhelm/Syntax_Qwen3_14B_Base_gsd_7") - Transformers
How to use Derinhelm/Syntax_Qwen3_14B_Base_gsd_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Derinhelm/Syntax_Qwen3_14B_Base_gsd_7") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Derinhelm/Syntax_Qwen3_14B_Base_gsd_7", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Derinhelm/Syntax_Qwen3_14B_Base_gsd_7 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Derinhelm/Syntax_Qwen3_14B_Base_gsd_7" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Derinhelm/Syntax_Qwen3_14B_Base_gsd_7", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Derinhelm/Syntax_Qwen3_14B_Base_gsd_7
- SGLang
How to use Derinhelm/Syntax_Qwen3_14B_Base_gsd_7 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 "Derinhelm/Syntax_Qwen3_14B_Base_gsd_7" \ --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": "Derinhelm/Syntax_Qwen3_14B_Base_gsd_7", "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 "Derinhelm/Syntax_Qwen3_14B_Base_gsd_7" \ --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": "Derinhelm/Syntax_Qwen3_14B_Base_gsd_7", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Derinhelm/Syntax_Qwen3_14B_Base_gsd_7 with Docker Model Runner:
docker model run hf.co/Derinhelm/Syntax_Qwen3_14B_Base_gsd_7
| !!python/object:parameters.Parameters | |
| batch_size: 32 | |
| config_name: /src/src/configs/config2.yaml | |
| dev_file_path: /src/src/data/grct_ru_gsd-ud-dev.json | |
| disable_qlora: false | |
| epochs: 10 | |
| experiment_number: 7 | |
| group_by_length: false | |
| is_instruct: false | |
| learning_rate: 0.0003 | |
| lora_alpha: 8 | |
| lora_dropout: 0.05 | |
| lora_r: 8 | |
| micro_batch_size: 8 | |
| model_name: /models/Qwen3-14B-Base | |
| root_output_dir_path: /src/src/results | |
| train_file_path: /src/src/data/grct_ru_gsd-ud-train.json | |
| treebank: gsd | |