Text Generation
Transformers
Safetensors
English
bananaall
novi-ai
language-model
pretrained-model
preview
small-language-model
bananamind-2-style
causal-lm
base-model
pretrained-from-scratch
project-kairo
triton
Instructions to use Novi-AI/Novi-Mini-Base-Preview-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Novi-AI/Novi-Mini-Base-Preview-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Novi-AI/Novi-Mini-Base-Preview-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Novi-AI/Novi-Mini-Base-Preview-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Novi-AI/Novi-Mini-Base-Preview-1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Novi-AI/Novi-Mini-Base-Preview-1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Novi-AI/Novi-Mini-Base-Preview-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Novi-AI/Novi-Mini-Base-Preview-1
- SGLang
How to use Novi-AI/Novi-Mini-Base-Preview-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 "Novi-AI/Novi-Mini-Base-Preview-1" \ --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": "Novi-AI/Novi-Mini-Base-Preview-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Novi-AI/Novi-Mini-Base-Preview-1" \ --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": "Novi-AI/Novi-Mini-Base-Preview-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Novi-AI/Novi-Mini-Base-Preview-1 with Docker Model Runner:
docker model run hf.co/Novi-AI/Novi-Mini-Base-Preview-1
Delete checkpoint-168000 folder
Browse files- checkpoint-168000/checkpoint-168000/config.json +0 -26
- checkpoint-168000/checkpoint-168000/generation_config.json +0 -12
- checkpoint-168000/checkpoint-168000/model.safetensors +0 -3
- checkpoint-168000/checkpoint-168000/optimizer.pt +0 -3
- checkpoint-168000/checkpoint-168000/rng_state.pth +0 -3
- checkpoint-168000/checkpoint-168000/scheduler.pt +0 -3
- checkpoint-168000/checkpoint-168000/tokenizer.json +0 -0
- checkpoint-168000/checkpoint-168000/tokenizer_config.json +0 -9
- checkpoint-168000/checkpoint-168000/trainer_state.json +0 -0
- checkpoint-168000/checkpoint-168000/training_args.bin +0 -3
checkpoint-168000/checkpoint-168000/config.json
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{
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"architecture_style": "bananamind2",
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"architectures": [
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"ProjectKairoMiniForCausalLM"
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],
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"bos_token_id": 1,
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"dtype": "float32",
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"eos_token_id": 2,
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"head_dim": 64,
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"hidden_size": 256,
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"intermediate_size": 768,
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"lft": false,
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"max_position_embeddings": 4096,
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"model_type": "bananaall",
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"num_attention_heads": 4,
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"num_hidden_layers": 10,
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"num_key_value_heads": 2,
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"pad_token_id": 0,
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"rms_norm_eps": 1e-06,
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"rope_theta": 100000.0,
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"ternary": false,
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"tie_word_embeddings": true,
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"transformers_version": "5.14.1",
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"use_cache": false,
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"vocab_size": 8192
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"transformers_version": "5.14.1",
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checkpoint-168000/checkpoint-168000/model.safetensors
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