Instructions to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF",
	filename="Llama-3.1-8B-Lexi-Uncensored_V2_F16.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 Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

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 Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

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 Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

Use Docker

docker model run hf.co/Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

LM Studio
Jan
Ollama
How to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with Ollama:
```
ollama run hf.co/Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16
```

Unsloth Studio

How to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-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 Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-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 Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF to start chatting

How to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

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": "Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

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 Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with Docker Model Runner:
```
docker model run hf.co/Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16
```

Lemonade

How to use Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2-GGUF:F16

Run and chat with the model

lemonade run user.Llama-3.1-8B-Lexi-Uncensored-V2-GGUF-F16

List all available models

lemonade list

Orenguteng commited on Sep 3, 2024

Commit

26b840c

verified ·

1 Parent(s): 93f5174

Update README.md

Browse files

Files changed (1) hide show

README.md +112 -3

README.md CHANGED Viewed

@@ -1,5 +1,100 @@
 ---
 license: llama3.1
 ---
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/644ad182f434a6a63b18eee6/7mnEJyioRzQaWz8xLM4KI.png)
@@ -8,18 +103,18 @@ VERSION 2 Update Notes:
 ---
 - More compliant
 - Smarter
-- Not fully evaluated, but scores higher on Winogrande compared to the original instruct model. 0.77901 vs 0.78848
 - For best response, use this system prompt (feel free to expand upon it as you wish):
 Think step by step with a logical reasoning and intellectual sense before you provide any response.
 - For more uncensored and compliant response, you can expand the system message differently, or simply enter a dot "." as system message.
-- IMPORTANT:
-Upon further investigation, the Q4 seems to have refusal issues sometimes.
 There seems to be some of the fine-tune loss happening due to the quantization. I will look into it for V3.
 Until then, I suggest you run F16 or Q8 if possible.
 GENERAL INFO:
 ---
@@ -43,3 +138,17 @@ If you find any issues or have suggestions for improvements, feel free to leave
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/644ad182f434a6a63b18eee6/uqJv-R1LeJEfMxi1nmTH5.png)

 ---
 license: llama3.1
+model-index:
+- name: Llama-3.1-8B-Lexi-Uncensored-V2
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 77.92
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 29.69
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 16.92
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 4.36
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 7.77
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 30.9
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
+      name: Open LLM Leaderboard
 ---
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/644ad182f434a6a63b18eee6/7mnEJyioRzQaWz8xLM4KI.png)
 ---
 - More compliant
 - Smarter
 - For best response, use this system prompt (feel free to expand upon it as you wish):
 Think step by step with a logical reasoning and intellectual sense before you provide any response.
 - For more uncensored and compliant response, you can expand the system message differently, or simply enter a dot "." as system message.
+- IMPORTANT: Upon further investigation, the Q4 seems to have refusal issues sometimes.
 There seems to be some of the fine-tune loss happening due to the quantization. I will look into it for V3.
 Until then, I suggest you run F16 or Q8 if possible.
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/644ad182f434a6a63b18eee6/zaHhRjsk3rvo_YewgXV2Z.png)
 GENERAL INFO:
 ---
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/644ad182f434a6a63b18eee6/uqJv-R1LeJEfMxi1nmTH5.png)
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Orenguteng__Llama-3.1-8B-Lexi-Uncensored-V2)
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |27.93|
+|IFEval (0-Shot)    |77.92|
+|BBH (3-Shot)       |29.69|
+|MATH Lvl 5 (4-Shot)|16.92|
+|GPQA (0-shot)      | 4.36|
+|MuSR (0-shot)      | 7.77|
+|MMLU-PRO (5-shot)  |30.90|