Instructions to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF", dtype="auto")

llama-cpp-python

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF",
	filename="GRAM-LLaMA3.2-3B-RewardModel.BF16.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF 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 prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF: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 prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF: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 prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M

Use Docker

docker model run hf.co/prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with Ollama:
```
ollama run hf.co/prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M
```

Unsloth Studio

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-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 prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-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 prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF to start chatting

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF: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": "prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF: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 prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF: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 "prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF: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 prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with Docker Model Runner:
```
docker model run hf.co/prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M
```

Lemonade

How to use prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull prithivMLmods/GRAM-LLaMA3.2-3B-RewardModel-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.GRAM-LLaMA3.2-3B-RewardModel-GGUF-Q4_K_M

List all available models

lemonade list

@@ -33,3 +33,16 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.BF16.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.F16.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.F32.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+GRAM-LLaMA3.2-3B-RewardModel.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text

prithivMLmods
/

GRAM-LLaMA3.2-3B-RewardModel-GGUF

Upload folder using huggingface_hub

+version https://git-lfs.github.com/spec/v1
+oid sha256:30be688c20d16ad91d94de3b0137eab600a96a100575a254296a9bea67760d09
+size 6433687552

+version https://git-lfs.github.com/spec/v1
+oid sha256:0e51d44b14d5a7d673cbbf0805fe1d2a786fb8b98ea8f9132991decaf820db02
+size 12858836992

+version https://git-lfs.github.com/spec/v1
+oid sha256:bb7035353a44d86a36f8bdc0cc7acd471264b70abec2ef05b8d69aa47acf4e4e
+size 1363935232

+version https://git-lfs.github.com/spec/v1
+oid sha256:8957f7e5660f314136f0d0e3f31e9dbdf776aba7f09c2bbb9082e3a23281e626
+size 1815347200

+version https://git-lfs.github.com/spec/v1
+oid sha256:21bef319a893aff2d240ec1dd65df7c775f0d5f3cdeba29e53f2a33eb3a9a7f5
+size 1687158784

+version https://git-lfs.github.com/spec/v1
+oid sha256:1cafe1eacc9015512dc12ce4ea5195c5b29849d3bba1ffced2d4efac721ea86d
+size 1542848512

+version https://git-lfs.github.com/spec/v1
+oid sha256:2c552e23fe04982400ad6416539b70fdcc44936dbb318725e7bcd50bc0c98ad4
+size 2019377152

+version https://git-lfs.github.com/spec/v1
+oid sha256:a4f503e684ba70bedbcc167c3e194c176524bc6183f1836c2c37bf12db102a01
+size 1928200192

+version https://git-lfs.github.com/spec/v1
+oid sha256:57fd776c194422dbb7b91f527075cc4391bbfc33cdf1c29801f0fbc3927db972
+size 2322153472

+version https://git-lfs.github.com/spec/v1
+oid sha256:5d520fbe74569583a22f996aaac10fe816d5504b6dd820737db6ed04ea81e36d
+size 2269511680

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

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

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

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:d59d8b2ef67fd35b45ecdd1145cafb1f2ba37dbc1ea4e4e8435afddf10f1bedc
+size 2643853312

+version https://git-lfs.github.com/spec/v1
+oid sha256:2e70c8737246ab1740d6d653f86517e464fab2f09fd67a9f484f0463267f14a1
+size 3421898752