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

Libraries

How to use codegeist/codegeist-llm with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-1.7B")
model = PeftModel.from_pretrained(base_model, "codegeist/codegeist-llm")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use codegeist/codegeist-llm 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 codegeist/codegeist-llm:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf codegeist/codegeist-llm:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf codegeist/codegeist-llm:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf codegeist/codegeist-llm:Q4_K_M

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 codegeist/codegeist-llm:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf codegeist/codegeist-llm:Q4_K_M

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 codegeist/codegeist-llm:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf codegeist/codegeist-llm:Q4_K_M

Use Docker

docker model run hf.co/codegeist/codegeist-llm:Q4_K_M

LM Studio
Jan

vLLM

How to use codegeist/codegeist-llm with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "codegeist/codegeist-llm"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codegeist/codegeist-llm",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/codegeist/codegeist-llm:Q4_K_M

Ollama
How to use codegeist/codegeist-llm with Ollama:
```
ollama run hf.co/codegeist/codegeist-llm:Q4_K_M
```

Unsloth Studio

How to use codegeist/codegeist-llm 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 codegeist/codegeist-llm 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 codegeist/codegeist-llm to start chatting

Using HuggingFace Spaces for Unsloth

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

How to use codegeist/codegeist-llm with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf codegeist/codegeist-llm:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "codegeist/codegeist-llm:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use codegeist/codegeist-llm with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf codegeist/codegeist-llm:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "codegeist/codegeist-llm:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use codegeist/codegeist-llm with Docker Model Runner:
```
docker model run hf.co/codegeist/codegeist-llm:Q4_K_M
```

Lemonade

How to use codegeist/codegeist-llm with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull codegeist/codegeist-llm:Q4_K_M

Run and chat with the model

lemonade run user.codegeist-llm-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use codegeist/codegeist-llm with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf codegeist/codegeist-llm:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default codegeist/codegeist-llm:Q4_K_M

Run Hermes

hermes

Atomic Chat

codegeist commited on 6 days ago

Commit

b7e4527

verified ·

1 Parent(s): ac7d2d4

Use final Codegeist LLM repository name

Browse files

Files changed (4) hide show

README.md +1 -1
SHA256SUMS +3 -3
evidence.json +2 -2
publication.json +1 -1

README.md CHANGED Viewed

@@ -76,7 +76,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 BASE_MODEL = "Qwen/Qwen3-1.7B"
 BASE_REVISION = "70d244cc86ccca08cf5af4e1e306ecf908b1ad5e"
-ADAPTER_MODEL = "codegeist/qwen3-1.7b-codegeist"
 ADAPTER_REVISION = "04d51edac56c6f1e068c644bfa8d014cadcecf9f"
 tokenizer = AutoTokenizer.from_pretrained(

 BASE_MODEL = "Qwen/Qwen3-1.7B"
 BASE_REVISION = "70d244cc86ccca08cf5af4e1e306ecf908b1ad5e"
+ADAPTER_MODEL = "codegeist/codegeist-llm"
 ADAPTER_REVISION = "04d51edac56c6f1e068c644bfa8d014cadcecf9f"
 tokenizer = AutoTokenizer.from_pretrained(

SHA256SUMS CHANGED Viewed

@@ -1,8 +1,8 @@
 9a66ed1f77d750a879b0e7b610bb15bb7c109fc1158448c0d7d543e7dbef421f  LICENSE
-0bcc6334e8f9cc8636d415150660b09b2d70c2a9cbfbb6261ac1aa73c894cf72  README.md
 d7ba9293f1820c63fe9e361ab3028390ce646125c898c008a4f8278eed8a4cb5  THIRD_PARTY_NOTICES.md
 42ef1e8075588b3732d0c00dd4c2a08a5e3498429d0e83192210e8006bdf15fb  adapter_config.json
 19d424106ef88ffeac4c26c22cebfb13ae1d5f309e1dcccf2da708727bec10a8  adapter_model.safetensors
-255898b19fc167bfe80d76f6d398eaa4e6e18c1d35f089d392aa97250701e3ec  evidence.json
 339a15a527229ab82bebce069cb96987a6e2ebb977261f03553759a8f979e57a  gpu-test-result.json
-67c29a7809b6ee9410f56da85f4a1cfb277e817cefbd1b72e9291b36f079759d  publication.json

 9a66ed1f77d750a879b0e7b610bb15bb7c109fc1158448c0d7d543e7dbef421f  LICENSE
+d3023f2f45f7fb5fc0a31fc4dfa361c08c820d81843c966aa256d50b80d9faf2  README.md
 d7ba9293f1820c63fe9e361ab3028390ce646125c898c008a4f8278eed8a4cb5  THIRD_PARTY_NOTICES.md
 42ef1e8075588b3732d0c00dd4c2a08a5e3498429d0e83192210e8006bdf15fb  adapter_config.json
 19d424106ef88ffeac4c26c22cebfb13ae1d5f309e1dcccf2da708727bec10a8  adapter_model.safetensors
+eb07672cd8662b58a9dcef56a92478cfbe2fee5fd13b66837a1d07a1ae7e20fd  evidence.json
 339a15a527229ab82bebce069cb96987a6e2ebb977261f03553759a8f979e57a  gpu-test-result.json
+f9259710bb9860f517de7951bedf622fdb4b8f9a76d7063cdae716a39aab65a3  publication.json

evidence.json CHANGED Viewed

@@ -307,8 +307,8 @@
     "public_repository_created": true
   },
   "publication": {
-    "repository": "codegeist/qwen3-1.7b-codegeist",
-    "url": "https://huggingface.co/codegeist/qwen3-1.7b-codegeist",
     "public": true,
     "public_access_verified_without_token": true,
     "adapter_artifact_revision": "04d51edac56c6f1e068c644bfa8d014cadcecf9f",

     "public_repository_created": true
   },
   "publication": {
+    "repository": "codegeist/codegeist-llm",
+    "url": "https://huggingface.co/codegeist/codegeist-llm",
     "public": true,
     "public_access_verified_without_token": true,
     "adapter_artifact_revision": "04d51edac56c6f1e068c644bfa8d014cadcecf9f",

publication.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "schema_version": 1,
-  "repository": "codegeist/qwen3-1.7b-codegeist",
   "initial_artifact_commit": "04d51edac56c6f1e068c644bfa8d014cadcecf9f",
   "base_model": {
     "id": "Qwen/Qwen3-1.7B",

 {
   "schema_version": 1,
+  "repository": "codegeist/codegeist-llm",
   "initial_artifact_commit": "04d51edac56c6f1e068c644bfa8d014cadcecf9f",
   "base_model": {
     "id": "Qwen/Qwen3-1.7B",