Text Generation
Transformers
Safetensors
GGUF
English
gemma4
image-text-to-text
bible
theology
gemma
ollama
cpt
sft
dpo
Instructions to use rhemabible/BibleAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rhemabible/BibleAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rhemabible/BibleAI")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("rhemabible/BibleAI") model = AutoModelForImageTextToText.from_pretrained("rhemabible/BibleAI") - llama-cpp-python
How to use rhemabible/BibleAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="rhemabible/BibleAI", filename="gguf/final_merged.BF16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use rhemabible/BibleAI with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rhemabible/BibleAI:BF16 # Run inference directly in the terminal: llama-cli -hf rhemabible/BibleAI:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rhemabible/BibleAI:BF16 # Run inference directly in the terminal: llama-cli -hf rhemabible/BibleAI:BF16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf rhemabible/BibleAI:BF16 # Run inference directly in the terminal: ./llama-cli -hf rhemabible/BibleAI:BF16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf rhemabible/BibleAI:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf rhemabible/BibleAI:BF16
Use Docker
docker model run hf.co/rhemabible/BibleAI:BF16
- LM Studio
- Jan
- vLLM
How to use rhemabible/BibleAI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rhemabible/BibleAI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rhemabible/BibleAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rhemabible/BibleAI:BF16
- SGLang
How to use rhemabible/BibleAI 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 "rhemabible/BibleAI" \ --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": "rhemabible/BibleAI", "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 "rhemabible/BibleAI" \ --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": "rhemabible/BibleAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use rhemabible/BibleAI with Ollama:
ollama run hf.co/rhemabible/BibleAI:BF16
- Unsloth Studio new
How to use rhemabible/BibleAI with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for rhemabible/BibleAI to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for rhemabible/BibleAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for rhemabible/BibleAI to start chatting
- Docker Model Runner
How to use rhemabible/BibleAI with Docker Model Runner:
docker model run hf.co/rhemabible/BibleAI:BF16
- Lemonade
How to use rhemabible/BibleAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull rhemabible/BibleAI:BF16
Run and chat with the model
lemonade run user.BibleAI-BF16
List all available models
lemonade list
| { | |
| "audio_token": "<|audio|>", | |
| "backend": "tokenizers", | |
| "boa_token": "<|audio>", | |
| "boi_token": "<|image>", | |
| "bos_token": "<bos>", | |
| "eoa_token": "<audio|>", | |
| "eoc_token": "<channel|>", | |
| "eoi_token": "<image|>", | |
| "eos_token": "<eos>", | |
| "eot_token": "<turn|>", | |
| "escape_token": "<|\"|>", | |
| "etc_token": "<tool_call|>", | |
| "etd_token": "<tool|>", | |
| "etr_token": "<tool_response|>", | |
| "extra_special_tokens": [], | |
| "image_token": "<|image|>", | |
| "is_local": true, | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "model_specific_special_tokens": { | |
| "audio_token": "<|audio|>", | |
| "boa_token": "<|audio>", | |
| "boi_token": "<|image>", | |
| "eoa_token": "<audio|>", | |
| "eoc_token": "<channel|>", | |
| "eoi_token": "<image|>", | |
| "eot_token": "<turn|>", | |
| "escape_token": "<|\"|>", | |
| "etc_token": "<tool_call|>", | |
| "etd_token": "<tool|>", | |
| "etr_token": "<tool_response|>", | |
| "image_token": "<|image|>", | |
| "soc_token": "<|channel>", | |
| "sot_token": "<|turn>", | |
| "stc_token": "<|tool_call>", | |
| "std_token": "<|tool>", | |
| "str_token": "<|tool_response>", | |
| "think_token": "<|think|>" | |
| }, | |
| "pad_token": "<pad>", | |
| "padding_side": "left", | |
| "processor_class": "Gemma4Processor", | |
| "soc_token": "<|channel>", | |
| "sot_token": "<|turn>", | |
| "stc_token": "<|tool_call>", | |
| "std_token": "<|tool>", | |
| "str_token": "<|tool_response>", | |
| "think_token": "<|think|>", | |
| "tokenizer_class": "GemmaTokenizer", | |
| "unk_token": "<unk>" | |
| } | |