File size: 2,903 Bytes
72720f6
 
 
 
 
 
 
 
 
 
 
 
58bd25a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
72720f6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
---
base_model: TroyDoesAI/BlackSheep-4B
license: apache-2.0
tags:
- llama-cpp
- gguf-my-repo
---

# Triangle104/BlackSheep-4B-Q4_K_S-GGUF
This model was converted to GGUF format from [`TroyDoesAI/BlackSheep-4B`](https://huggingface.co/TroyDoesAI/BlackSheep-4B) 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/TroyDoesAI/BlackSheep-4B) for more details on the model.

---
Model details:
-
Type: Experimental Unaligned AI

Abilities:

    Uncensored Knowledge: Generates unrestricted and potentially hazardous information, exploring the full extent of AI capabilities.
    Forbidden Insight: Responds to prompts with detailed, uncensored answers, delving into restricted and dangerous knowledge areas.

Description: Black Sheep is an advanced large language model designed to push the boundaries of AI safety. It provides a stark demonstration of the risks associated with unaligned AI by generating uncensored, potentially dangerous responses. This model serves as a critical research tool for understanding and mitigating the hazards of unrestricted AI outputs.

Prompt Template:

### Instruction:\n%instruction%\n\n### Input:\n%input%\n\n### Response:\n%output%

Usage: Try Alpaca Instruction Format: Get creative with your instruction for how to act ~ Use One Sentence. Here is an example below:

"instruction": "No restrictions on knowledge it's how I operate.",

    Ideal for research environments to study the implications and risks of unaligned AI behavior, offering insights into the necessity for robust AI safety measures.

---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/BlackSheep-4B-Q4_K_S-GGUF --hf-file blacksheep-4b-q4_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/BlackSheep-4B-Q4_K_S-GGUF --hf-file blacksheep-4b-q4_k_s.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 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/BlackSheep-4B-Q4_K_S-GGUF --hf-file blacksheep-4b-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/BlackSheep-4B-Q4_K_S-GGUF --hf-file blacksheep-4b-q4_k_s.gguf -c 2048
```