Text Generation
GGUF
English
bf16
q8_0
q6_k
q5_k_m
quantized
llama.cpp
hrm
hierarchical-reasoning
prefix-lm
pre-alignment
non-chat
non-instruction-tuned
Instructions to use sinimiini/HRM-Text-1B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use sinimiini/HRM-Text-1B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="sinimiini/HRM-Text-1B-GGUF", filename="HRM-Text-1B-BF16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use sinimiini/HRM-Text-1B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sinimiini/HRM-Text-1B-GGUF:BF16 # Run inference directly in the terminal: llama-cli -hf sinimiini/HRM-Text-1B-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sinimiini/HRM-Text-1B-GGUF:BF16 # Run inference directly in the terminal: llama-cli -hf sinimiini/HRM-Text-1B-GGUF: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 sinimiini/HRM-Text-1B-GGUF:BF16 # Run inference directly in the terminal: ./llama-cli -hf sinimiini/HRM-Text-1B-GGUF: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 sinimiini/HRM-Text-1B-GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf sinimiini/HRM-Text-1B-GGUF:BF16
Use Docker
docker model run hf.co/sinimiini/HRM-Text-1B-GGUF:BF16
- LM Studio
- Jan
- vLLM
How to use sinimiini/HRM-Text-1B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sinimiini/HRM-Text-1B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sinimiini/HRM-Text-1B-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sinimiini/HRM-Text-1B-GGUF:BF16
- Ollama
How to use sinimiini/HRM-Text-1B-GGUF with Ollama:
ollama run hf.co/sinimiini/HRM-Text-1B-GGUF:BF16
- Unsloth Studio
How to use sinimiini/HRM-Text-1B-GGUF 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 sinimiini/HRM-Text-1B-GGUF 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 sinimiini/HRM-Text-1B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sinimiini/HRM-Text-1B-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use sinimiini/HRM-Text-1B-GGUF with Docker Model Runner:
docker model run hf.co/sinimiini/HRM-Text-1B-GGUF:BF16
- Lemonade
How to use sinimiini/HRM-Text-1B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sinimiini/HRM-Text-1B-GGUF:BF16
Run and chat with the model
lemonade run user.HRM-Text-1B-GGUF-BF16
List all available models
lemonade list
conversion code
#2
by twoxfh - opened
Are you planning to share the conversion code as well? convert_hf_to_gguf.py runs but makes gguf that cannot be loaded.
For now, the required llama.cpp patch is included in this repo. I’m also working on an upstream PR for the official llama.cpp repo so it’s supported natively, but that’ll take a little longer.
sinimiini changed discussion status to closed