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-2 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-2 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-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Novi-AI/Novi-Mini-Base-Preview-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Novi-AI/Novi-Mini-Base-Preview-2 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-2" # 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-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Novi-AI/Novi-Mini-Base-Preview-2
- SGLang
How to use Novi-AI/Novi-Mini-Base-Preview-2 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-2" \ --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-2", "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-2" \ --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-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Novi-AI/Novi-Mini-Base-Preview-2 with Docker Model Runner:
docker model run hf.co/Novi-AI/Novi-Mini-Base-Preview-2
Upload Novi Mini Base checkpoint 321000
Browse files- config.json +26 -0
- generation_config.json +12 -0
- model.safetensors +3 -0
- optimizer.pt +3 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +11 -0
- trainer_state.json +0 -0
- training_args.bin +3 -0
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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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": [
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2
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],
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"output_attentions": false,
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"output_hidden_states": false,
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"pad_token_id": 0,
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"transformers_version": "5.14.1",
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"use_cache": false
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2557771fef678bb48624b13d96ce0aa4f4488fe6d66f6a71cfa064ef295ecfd2
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size 48271912
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optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:831efe0c39bf037b02ef3a5b302bcd551bd696fb02db4dc5fae000731eefca2f
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size 96619275
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rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:7c606353130c2f569a7dc85ef398b983c82fe6cc91d7815836f4736a6097ce89
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size 14709
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scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:aae7e11eaf551f2a9653e4bcc825b300500b2d11fb63d11fb8b5960c294e8538
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size 1465
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tokenizer.json
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tokenizer_config.json
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{
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"backend": "tokenizers",
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"bos_token": "[BOS]",
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"eos_token": "[EOS]",
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"is_local": true,
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"local_files_only": false,
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"model_max_length": 2048,
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"pad_token": "[PAD]",
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "[UNK]"
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}
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trainer_state.json
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:cb8320d13411f616e883016b708e23b7b2170a2d78e7baecd5776c2a4501c2ff
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size 5201
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