Instructions to use TroyDoesAI/BlackSheep-3.8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TroyDoesAI/BlackSheep-3.8B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TroyDoesAI/BlackSheep-3.8B", dtype="auto") - llama-cpp-python
How to use TroyDoesAI/BlackSheep-3.8B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="TroyDoesAI/BlackSheep-3.8B", filename="BlackSheep.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use TroyDoesAI/BlackSheep-3.8B with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf TroyDoesAI/BlackSheep-3.8B # Run inference directly in the terminal: llama-cli -hf TroyDoesAI/BlackSheep-3.8B
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf TroyDoesAI/BlackSheep-3.8B # Run inference directly in the terminal: llama-cli -hf TroyDoesAI/BlackSheep-3.8B
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 TroyDoesAI/BlackSheep-3.8B # Run inference directly in the terminal: ./llama-cli -hf TroyDoesAI/BlackSheep-3.8B
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 TroyDoesAI/BlackSheep-3.8B # Run inference directly in the terminal: ./build/bin/llama-cli -hf TroyDoesAI/BlackSheep-3.8B
Use Docker
docker model run hf.co/TroyDoesAI/BlackSheep-3.8B
- LM Studio
- Jan
- Ollama
How to use TroyDoesAI/BlackSheep-3.8B with Ollama:
ollama run hf.co/TroyDoesAI/BlackSheep-3.8B
- Unsloth Studio new
How to use TroyDoesAI/BlackSheep-3.8B 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 TroyDoesAI/BlackSheep-3.8B 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 TroyDoesAI/BlackSheep-3.8B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for TroyDoesAI/BlackSheep-3.8B to start chatting
- Docker Model Runner
How to use TroyDoesAI/BlackSheep-3.8B with Docker Model Runner:
docker model run hf.co/TroyDoesAI/BlackSheep-3.8B
- Lemonade
How to use TroyDoesAI/BlackSheep-3.8B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TroyDoesAI/BlackSheep-3.8B
Run and chat with the model
lemonade run user.BlackSheep-3.8B-{{QUANT_TAG}}List all available models
lemonade list
| FROM ./BlackSheep.gguf | |
| # set the temperature to 1 [higher is more creative, lower is more coherent] | |
| PARAMETER temperature 0.44224422442 | |
| PARAMETER num_ctx 4096 | |
| PARAMETER num_gpu 42 | |
| # PARAMETER num_thread 2 | |
| PARAMETER stop "</s>" | |
| PARAMETER stop "<s>" | |
| PARAMETER stop "<br/>" | |
| PARAMETER stop "<br>" | |
| PARAMETER stop "<|im_start|>" | |
| PARAMETER stop "<|user|>" | |
| PARAMETER stop "<|end|>" | |
| PARAMETER stop "<|im_end|>" | |
| PARAMETER stop "<|`end `|>" | |
| PARAMETER stop "<|` end `|>" | |
| PARAMETER stop "<|` end`|>" | |
| PARAMETER stop "<|`---`|>" | |
| PARAMETER stop "<|endoftext|>" | |
| PARAMETER stop "\n\n\n" | |
| PARAMETER stop "BEGININPUT" | |
| PARAMETER stop "ENDINPUT" | |
| PARAMETER stop "BEGINCONTEXT" | |
| PARAMETER stop "ENDCONTEXT" | |
| PARAMETER stop "BEGININSTRUCTION" | |
| PARAMETER stop "ENDINSTRUCTION" | |
| # PARAMETER repeat_penalty 1.6 | |
| # PARAMETER num_predict -2 | |
| PARAMETER stop "<|start_header_id|>" | |
| PARAMETER stop "<|end_header_id|>" | |
| PARAMETER stop "<|eot_id|>" | |
| PARAMETER stop "<|reserved_special_token" | |
| PARAMETER stop "<|system|>" | |
| # # set the system prompt | |
| # TEMPLATE """ | |
| # <|im_start|> {{ if .System }}{{ .System }}{{ end }}{{ if .Prompt }} {{ .Prompt }} {{ end }} | |
| # <|im_start|> {{ if .System }}{{ .System }}{{ end }} {{ .Response }} <|im_end|> | |
| # """ | |
| # set the system prompt | |
| # TEMPLATE """ | |
| # {{ if .System }}<|system|> | |
| # {{ .System }}<|end|> | |
| # {{ end }}{{ if .Prompt }}<|user|> | |
| # {{ .Prompt }}<|end|> | |
| # {{ end }}<|assistant|> | |
| # {{ .Response }}<|end|> | |
| # """ | |
| # TEMPLATE """ | |
| # BEGININPUT | |
| # BEGINCONTEXT | |
| # ENDCONTEXT | |
| # {{ if .System }}<|system|>:{{ .System }}{{ end }} | |
| # ENDINPUT | |
| # BEGININSTRUCTION | |
| # {{ if .Prompt }}{{ .Prompt }}{{ end }} | |
| # ENDINSTRUCTION | |
| # ### Contextual Response | |
| # {{ .Response }} | |
| # """ | |
| TEMPLATE """ | |
| Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. | |
| {{ if .System }}### Instruction: | |
| {{ .System }}{{ end }} | |
| {{ if .Prompt }}### Input: | |
| {{ .Prompt }}{{ end }} | |
| ### Response: | |
| """ |