Text Generation
Transformers
PyTorch
Safetensors
llama
conversational
Eval Results (legacy)
text-generation-inference
Instructions to use ConvexAI/Luminex-34B-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConvexAI/Luminex-34B-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ConvexAI/Luminex-34B-v0.1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("ConvexAI/Luminex-34B-v0.1") model = AutoModelForMultimodalLM.from_pretrained("ConvexAI/Luminex-34B-v0.1") 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 Settings
- vLLM
How to use ConvexAI/Luminex-34B-v0.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ConvexAI/Luminex-34B-v0.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ConvexAI/Luminex-34B-v0.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ConvexAI/Luminex-34B-v0.1
- SGLang
How to use ConvexAI/Luminex-34B-v0.1 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 "ConvexAI/Luminex-34B-v0.1" \ --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": "ConvexAI/Luminex-34B-v0.1", "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 "ConvexAI/Luminex-34B-v0.1" \ --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": "ConvexAI/Luminex-34B-v0.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ConvexAI/Luminex-34B-v0.1 with Docker Model Runner:
docker model run hf.co/ConvexAI/Luminex-34B-v0.1
| url: https://huggingface.co/ConvexAI/Luminex-34B-v0.1 | |
| branch: main | |
| download date: 2024-02-16 22:23:47 | |
| sha256sum: | |
| be4b3c335c2880646317b4c5ac2f5ac35258a200def72655885aa708984cca18 pytorch_model-00001-of-00007.bin | |
| dc6aa2bb8e35ccd0568d4f7f3e0d266194965a2ef4d3aa9535a64d1775a7df04 pytorch_model-00002-of-00007.bin | |
| 48b2ef8ba7102eccbef4120b8e84b9ff3272834e9f51f272f685faf1f7e47e73 pytorch_model-00003-of-00007.bin | |
| 5a0078a6307f7b722aeebc59d2e0f720e460aaa7adb6fc01f1bb58e8dc962ec7 pytorch_model-00004-of-00007.bin | |
| 7c9b09724b10f6add24491b3ddb19f625281a5b4f26eac039addf2e253961b13 pytorch_model-00005-of-00007.bin | |
| 7dde6e73ea8b49f39c5d7d1e75e94cd1e5ae05b8d300a8a1c36d2d031c388fc7 pytorch_model-00006-of-00007.bin | |
| 974e5e72a9a6bd776901488f8fd6c3bd923d4e0dd2b4dae83015eb260b10f580 pytorch_model-00007-of-00007.bin | |
| 386c49cf943d71aa110361135338c50e38beeff0a66593480421f37b319e1a39 tokenizer.model | |