Instructions to use leafspark/Reflection-Llama-3.1-70B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use leafspark/Reflection-Llama-3.1-70B-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 leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

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 leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

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 leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

Use Docker

docker model run hf.co/leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

LM Studio
Jan

vLLM

How to use leafspark/Reflection-Llama-3.1-70B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "leafspark/Reflection-Llama-3.1-70B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "leafspark/Reflection-Llama-3.1-70B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

Ollama
How to use leafspark/Reflection-Llama-3.1-70B-GGUF with Ollama:
```
ollama run hf.co/leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S
```
Unsloth Desktop

How to use leafspark/Reflection-Llama-3.1-70B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

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": "leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use leafspark/Reflection-Llama-3.1-70B-GGUF with Docker Model Runner:
```
docker model run hf.co/leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S
```

Lemonade

How to use leafspark/Reflection-Llama-3.1-70B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

Run and chat with the model

lemonade run user.Reflection-Llama-3.1-70B-GGUF-Q4_K_S

List all available models

lemonade list

Hermes Agent

How to use leafspark/Reflection-Llama-3.1-70B-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 leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

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 leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use leafspark/Reflection-Llama-3.1-70B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S

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 "leafspark/Reflection-Llama-3.1-70B-GGUF:Q4_K_S" \
  --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"

leafspark commited on Sep 9, 2024

Commit

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1 Parent(s): 52249b8

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README.md +28 -6

README.md CHANGED Viewed

@@ -2,6 +2,15 @@
 license: llama3.1
 language:
 - en
 base_model: mattshumer/ref_70_e3
 pipeline_tag: text-generation
 library_name: ggml
@@ -22,22 +31,35 @@ GGUF quantized models of [mattshumer/ref_70_e3](https://huggingface.co/mattshume
 | Quantization | Size   | Split | iMatrix |
 | ------------ | ------ | ----- | ------- |
 | FP16         | 141GB  | true  | false   |
-| Q8_0_L       | 73GB   | true  | false   |
-| Q6_K_L       | 56.2GB | true  | false   |
 | Q6_K         | ??.?GB | true  | false   |
 | Q5_K_L       | 52.6GB | true  | false   |
 | Q5_K_M       | ??.?GB | true  | false   |
-| Q5_K_S       | ??.?GB | false | false   |
-| Q4_K_L       | 42.1GB | false | false   |
 | Q4_K_M       | ??.?GB | false | false   |
 | Q4_K_S       | ??.?GB | false | false   |
-| Q3_K_XL      | ??.?GB | false | false   |
-| Q3_K_L       | 40GB   | false | false   |
 | Q3_K_M       | ??.?GB | false | false   |
 | Q3_K_S       | ??.?GB | false | false   |
 | Q2_K_L       | 29.4GB | false | false   |
 | Q2_K         | ??.?GB | false | false   |
 | Q2_K_S       | ??.?GB | false | true    |
 The `_L` or `_XL` suffix means that the token embeddings and output weight are at fp16 precision.

 license: llama3.1
 language:
 - en
+- de
+- fr
+- it
+- pt
+- hi
+- es
+- th
+tags:
+- llama
 base_model: mattshumer/ref_70_e3
 pipeline_tag: text-generation
 library_name: ggml
 | Quantization | Size   | Split | iMatrix |
 | ------------ | ------ | ----- | ------- |
 | FP16         | 141GB  | true  | false   |
+| Q8_0_L       | ??.?GB | true  | false   |
+| Q8_0         | ??.?GB | true  | false   |
+| Q6_K_L       | ??.?GB | true  | false   |
 | Q6_K         | ??.?GB | true  | false   |
 | Q5_K_L       | 52.6GB | true  | false   |
 | Q5_K_M       | ??.?GB | true  | false   |
+| Q5_K_S       | 48.7GB | false | false   |
+| Q4_K_L       | 45.3GB | false | false   |
 | Q4_K_M       | ??.?GB | false | false   |
 | Q4_K_S       | ??.?GB | false | false   |
+| IQ4_NL       | ??.?GB | false | true    |
+| IQ4_XS       | ??.?GB | false | true    |
+| Q3_K_XL      | 37.2GB | false | false   |
+| Q3_K_L       | ??.?GB | false | false   |
 | Q3_K_M       | ??.?GB | false | false   |
+| IQ3_M        | ??.?GB | false | true    |
 | Q3_K_S       | ??.?GB | false | false   |
+| IQ3_S        | ??.?GB | false | true    |
 | Q2_K_L       | 29.4GB | false | false   |
+| IQ3_XS       | ??.?GB | false | true    |
+| IQ3_XXS      | ??.?GB | false | true    |
 | Q2_K         | ??.?GB | false | false   |
 | Q2_K_S       | ??.?GB | false | true    |
+| IQ2_M        | ??.?GB | false | true    |
+| IQ2_S        | ??.?GB | false | true    |
+| IQ2_XS       | ??.?GB | false | true    |
+| IQ2_XXS      | ??.?GB | false | true    |
+| IQ1_M        | ??.?GB | false | true    |
+| IQ1_S        | ??.?GB | false | true    |
 The `_L` or `_XL` suffix means that the token embeddings and output weight are at fp16 precision.