Text Generation
Transformers
Safetensors
PyTorch
lance_ai
gpt
causal-lm
lance-ai
conversational
custom_code
Instructions to use NeuraCraft/Lance-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuraCraft/Lance-AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NeuraCraft/Lance-AI", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("NeuraCraft/Lance-AI", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use NeuraCraft/Lance-AI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NeuraCraft/Lance-AI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NeuraCraft/Lance-AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/NeuraCraft/Lance-AI
- SGLang
How to use NeuraCraft/Lance-AI 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 "NeuraCraft/Lance-AI" \ --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": "NeuraCraft/Lance-AI", "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 "NeuraCraft/Lance-AI" \ --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": "NeuraCraft/Lance-AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use NeuraCraft/Lance-AI with Docker Model Runner:
docker model run hf.co/NeuraCraft/Lance-AI
Update lance_ai_model.py
Browse files- lance_ai_model.py +2 -0
lance_ai_model.py
CHANGED
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@@ -24,7 +24,9 @@ class LanceAIConfig(PretrainedConfig):
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super().__init__(**kwargs)
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self.vocab_size = vocab_size
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self.hidden_size = hidden_size
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self.num_layers = num_layers
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self.num_heads = num_heads
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self.intermediate_size = intermediate_size
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self.hidden_dropout = hidden_dropout
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super().__init__(**kwargs)
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self.vocab_size = vocab_size
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self.hidden_size = hidden_size
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+
self.num_hidden_layers = num_layers
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self.num_layers = num_layers
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self.num_attention_heads = num_heads
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self.num_heads = num_heads
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self.intermediate_size = intermediate_size
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self.hidden_dropout = hidden_dropout
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