Text Generation
Safetensors
GGUF
English
llama
sql
nl2sql
code-generation
fine-tuning
local-first
postgresql
conversational
Instructions to use Interchained/imagine-v12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Interchained/imagine-v12 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Interchained/imagine-v12:Q4_K_M # Run inference directly in the terminal: llama cli -hf Interchained/imagine-v12:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Interchained/imagine-v12:Q4_K_M # Run inference directly in the terminal: llama cli -hf Interchained/imagine-v12:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf Interchained/imagine-v12:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf Interchained/imagine-v12:Q4_K_M
Use Docker
docker model run hf.co/Interchained/imagine-v12:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use Interchained/imagine-v12 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Interchained/imagine-v12" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Interchained/imagine-v12", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Interchained/imagine-v12:Q4_K_M
- Ollama
How to use Interchained/imagine-v12 with Ollama:
ollama run hf.co/Interchained/imagine-v12:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Interchained/imagine-v12 with Docker Model Runner:
docker model run hf.co/Interchained/imagine-v12:Q4_K_M
- Lemonade
How to use Interchained/imagine-v12 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Interchained/imagine-v12:Q4_K_M
Run and chat with the model
lemonade run user.imagine-v12-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 777 Bytes
0f1abe1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 32013,
"dtype": "bfloat16",
"eos_token_id": 32021,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 2048,
"initializer_range": 0.02,
"intermediate_size": 5504,
"max_position_embeddings": 16384,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 16,
"num_hidden_layers": 24,
"num_key_value_heads": 16,
"pad_token_id": null,
"pretraining_tp": 1,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"factor": 4.0,
"rope_theta": 100000,
"rope_type": "linear",
"type": "linear"
},
"tie_word_embeddings": false,
"transformers_version": "5.19.0",
"use_cache": false,
"vocab_size": 32256
}
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