Instructions to use openensemble/plan-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openensemble/plan-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="openensemble/plan-gguf",
	filename="openensemble-plan-360m-v2.q8_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use openensemble/plan-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf openensemble/plan-gguf:Q8_0
# Run inference directly in the terminal:
llama-cli -hf openensemble/plan-gguf:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf openensemble/plan-gguf:Q8_0
# Run inference directly in the terminal:
llama-cli -hf openensemble/plan-gguf:Q8_0

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 openensemble/plan-gguf:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf openensemble/plan-gguf:Q8_0

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 openensemble/plan-gguf:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf openensemble/plan-gguf:Q8_0

Use Docker

docker model run hf.co/openensemble/plan-gguf:Q8_0

LM Studio
Jan
Ollama
How to use openensemble/plan-gguf with Ollama:
```
ollama run hf.co/openensemble/plan-gguf:Q8_0
```

Unsloth Studio new

How to use openensemble/plan-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 openensemble/plan-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 openensemble/plan-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for openensemble/plan-gguf to start chatting

Docker Model Runner
How to use openensemble/plan-gguf with Docker Model Runner:
```
docker model run hf.co/openensemble/plan-gguf:Q8_0
```

Lemonade

How to use openensemble/plan-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull openensemble/plan-gguf:Q8_0

Run and chat with the model

lemonade run user.plan-gguf-Q8_0

List all available models

lemonade list

openensemble commited on 10 days ago

Commit

b7eb808

verified ·

1 Parent(s): f90dd0e

Add plan v3 (v14b retrain, weekday phrasings + military time + clean reschedule labels, 2026-04-27)

Browse files

Files changed (2) hide show

.gitattributes +1 -0
openensemble-plan-v3.q8_0.gguf +3 -0

.gitattributes CHANGED Viewed

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 openensemble-plan-v12.q8_0.gguf filter=lfs diff=lfs merge=lfs -text

 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 openensemble-plan-v12.q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+openensemble-plan-v3.q8_0.gguf filter=lfs diff=lfs merge=lfs -text

openensemble-plan-v3.q8_0.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:1739500eed7515c6fe9f114eb4176f7e37360a523b6946b8f3ed00eea60fc433
+size 144813408