Instructions to use madhuHuggingface/functiongemma-ec2-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use madhuHuggingface/functiongemma-ec2-finetuned with Transformers:

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("madhuHuggingface/functiongemma-ec2-finetuned", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use madhuHuggingface/functiongemma-ec2-finetuned 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 madhuHuggingface/functiongemma-ec2-finetuned:Q8_0
# Run inference directly in the terminal:
llama cli -hf madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf madhuHuggingface/functiongemma-ec2-finetuned:Q8_0
# Run inference directly in the terminal:
llama cli -hf madhuHuggingface/functiongemma-ec2-finetuned: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 madhuHuggingface/functiongemma-ec2-finetuned:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf madhuHuggingface/functiongemma-ec2-finetuned: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 madhuHuggingface/functiongemma-ec2-finetuned:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

Use Docker

docker model run hf.co/madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

LM Studio
Jan
Ollama
How to use madhuHuggingface/functiongemma-ec2-finetuned with Ollama:
```
ollama run hf.co/madhuHuggingface/functiongemma-ec2-finetuned:Q8_0
```
Unsloth Desktop

How to use madhuHuggingface/functiongemma-ec2-finetuned with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "madhuHuggingface/functiongemma-ec2-finetuned:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use madhuHuggingface/functiongemma-ec2-finetuned with Docker Model Runner:
```
docker model run hf.co/madhuHuggingface/functiongemma-ec2-finetuned:Q8_0
```

Lemonade

How to use madhuHuggingface/functiongemma-ec2-finetuned with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

Run and chat with the model

lemonade run user.functiongemma-ec2-finetuned-Q8_0

List all available models

lemonade list

Hermes Agent

How to use madhuHuggingface/functiongemma-ec2-finetuned with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

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 madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use madhuHuggingface/functiongemma-ec2-finetuned with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf madhuHuggingface/functiongemma-ec2-finetuned:Q8_0

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 "madhuHuggingface/functiongemma-ec2-finetuned:Q8_0" \
  --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"

madhuHuggingface commited on Apr 24

Commit

4e36a4d

verified ·

1 Parent(s): 7294eee

Training in progress, step 100

Browse files

Files changed (3) hide show

adapter_model.safetensors +1 -1
tokenizer_config.json +1 -1
training_args.bin +1 -1

adapter_model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4cb557daf6d75831c1e4da4535fdc7690f5ccf481dc20f270738e296bd0bdd5c
 size 60785144

 version https://git-lfs.github.com/spec/v1
+oid sha256:e518e2738d075373937c38f2850f0e79d762b66ba96fa90d5c2a5a02a2cad24a
 size 60785144

tokenizer_config.json CHANGED Viewed

@@ -51345,7 +51345,7 @@
   "image_token": "<image_soft_token>",
   "model_max_length": 32768,
   "pad_token": "<pad>",
-  "padding_side": "left",
   "sfr_token": "<start_function_response>",
   "sp_model_kwargs": null,
   "spaces_between_special_tokens": false,

   "image_token": "<image_soft_token>",
   "model_max_length": 32768,
   "pad_token": "<pad>",
+  "padding_side": "right",
   "sfr_token": "<start_function_response>",
   "sp_model_kwargs": null,
   "spaces_between_special_tokens": false,

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:abc526e0d2d37a3bd6eaa08f79cb4da62578b543694bda368ffceb921df35e95
 size 6353

 version https://git-lfs.github.com/spec/v1
+oid sha256:bad76c15491571a2b0d904f43b98d3ec2521c42abf54bc17c579eedfa7b8332a
 size 6353