Instructions to use Enferlain/ellmo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Enferlain/ellmo with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Enferlain/ellmo", filename="13b/Fimbulvetr-11B-v2-Test-14.q6_K.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Enferlain/ellmo with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Enferlain/ellmo:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Enferlain/ellmo:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Enferlain/ellmo:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Enferlain/ellmo: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 Enferlain/ellmo:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Enferlain/ellmo: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 Enferlain/ellmo:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Enferlain/ellmo:Q4_K_M
Use Docker
docker model run hf.co/Enferlain/ellmo:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Enferlain/ellmo with Ollama:
ollama run hf.co/Enferlain/ellmo:Q4_K_M
- Unsloth Studio
How to use Enferlain/ellmo 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 Enferlain/ellmo 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 Enferlain/ellmo to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Enferlain/ellmo to start chatting
- Docker Model Runner
How to use Enferlain/ellmo with Docker Model Runner:
docker model run hf.co/Enferlain/ellmo:Q4_K_M
- Lemonade
How to use Enferlain/ellmo with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Enferlain/ellmo:Q4_K_M
Run and chat with the model
lemonade run user.ellmo-Q4_K_M
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files- 13b/13b.kcpps +1 -0
- 13b/MLewdBoros-L2-13B.q5_K_M.gguf +3 -0
- 13b/Mistral-11B-AirOmniMix.q6_k.gguf +3 -0
- 13b/airoboros-l2-13b-2.1.Q5_K_M.gguf +3 -0
- 13b/airoboros-l2-13b-gpt4-m2.0.ggmlv3.q4_K_M.bin +3 -0
- 13b/alma-13b.Q5_K_M.gguf +3 -0
- 13b/amethyst-13b-mistral.Q5_K_M.gguf +3 -0
- 13b/athena-v1.Q5_K_M.gguf +3 -0
- 13b/athnete-13b.Q5_K_M.gguf +3 -0
- 13b/chronos-13b-v2.ggmlv3.q4_K_M.bin +3 -0
- 13b/chronos-beluga-v2-13b.ggmlv3.q4_K_M.bin +3 -0
- 13b/crestfall-echidna-v0.3-L2-13b-q5_k_m.gguf +3 -0
- 13b/crestfall-xwin-mlewd-v0.2-L2-13b-q5_k_m.gguf +3 -0
- 13b/echidna-tiefigther-25.Q5_K_M.gguf +3 -0
- 13b/hermes-kimiko-13b.ggmlv3.q5_K_M.bin +3 -0
- 13b/llama-2-13b-ensemble-v6.Q5_K_M.gguf +3 -0
- 13b/magpie-13b-Q5_K_M.gguf +3 -0
13b/13b.kcpps
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