Instructions to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF with Transformers:

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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 lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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 lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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 lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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 lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M
```
Unsloth Desktop

How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M

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": "lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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 lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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 lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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 "lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-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"

mjbuehler commited on Feb 11

Commit

eeccd22

verified ·

1 Parent(s): 267a56c

Update README.md

Browse files

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README.md +7 -6

README.md CHANGED Viewed

@@ -4,9 +4,10 @@ library_name: transformers
 tags:
 - llama-cpp
 - gguf-my-repo
 ---
-# rachelkluu/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF
 This model was converted to GGUF format from [`lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024`](https://huggingface.co/lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024) for more details on the model.
@@ -21,12 +22,12 @@ Invoke the llama.cpp server or the CLI.
 ### CLI:
 ```bash
-llama-cli --hf-repo rachelkluu/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -p "The meaning to life and the universe is"
 ```
 ### Server:
 ```bash
-llama-server --hf-repo rachelkluu/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -c 2048
 ```
 Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
@@ -43,9 +44,9 @@ cd llama.cpp && LLAMA_CURL=1 make
 Step 3: Run inference through the main binary.
 ```
-./llama-cli --hf-repo rachelkluu/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -p "The meaning to life and the universe is"
 ```
 or
 ```
-./llama-server --hf-repo rachelkluu/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -c 2048
-```

 tags:
 - llama-cpp
 - gguf-my-repo
+license: apache-2.0
 ---
+# lamm-mit//Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF
 This model was converted to GGUF format from [`lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024`](https://huggingface.co/lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024) for more details on the model.
 ### CLI:
 ```bash
+llama-cli --hf-repo lamm-mit//Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -p "The meaning to life and the universe is"
 ```
 ### Server:
 ```bash
+llama-server --hf-repo lamm-mit//Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -c 2048
 ```
 Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
 Step 3: Run inference through the main binary.
 ```
+./llama-cli --hf-repo lamm-mit//Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -p "The meaning to life and the universe is"
 ```
 or
 ```
+./llama-server --hf-repo lamm-mit//Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF --hf-file llama3.1-8b-instruct-cpt-sft-dpo-09022024-q4_k_m.gguf -c 2048
+```