Instructions to use jazeelmohd/mobileo_android with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use jazeelmohd/mobileo_android with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="jazeelmohd/mobileo_android", filename="text_encoder.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 jazeelmohd/mobileo_android 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 jazeelmohd/mobileo_android:F16 # Run inference directly in the terminal: llama cli -hf jazeelmohd/mobileo_android:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jazeelmohd/mobileo_android:F16 # Run inference directly in the terminal: llama cli -hf jazeelmohd/mobileo_android: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 jazeelmohd/mobileo_android:F16 # Run inference directly in the terminal: ./llama-cli -hf jazeelmohd/mobileo_android: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 jazeelmohd/mobileo_android:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf jazeelmohd/mobileo_android:F16
Use Docker
docker model run hf.co/jazeelmohd/mobileo_android:F16
- LM Studio
- Jan
- Ollama
How to use jazeelmohd/mobileo_android with Ollama:
ollama run hf.co/jazeelmohd/mobileo_android:F16
- Unsloth Studio
How to use jazeelmohd/mobileo_android 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 jazeelmohd/mobileo_android 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 jazeelmohd/mobileo_android to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jazeelmohd/mobileo_android to start chatting
- Atomic Chat new
- Docker Model Runner
How to use jazeelmohd/mobileo_android with Docker Model Runner:
docker model run hf.co/jazeelmohd/mobileo_android:F16
- Lemonade
How to use jazeelmohd/mobileo_android with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jazeelmohd/mobileo_android:F16
Run and chat with the model
lemonade run user.mobileo_android-F16
List all available models
lemonade list
| { | |
| "_class_name": "CustomScheduler", | |
| "_diffusers_version": "0.32.0.dev0", | |
| "algorithm_type": "custom_v1", | |
| "beta_end": 0.02, | |
| "beta_schedule": "linear", | |
| "beta_start": 0.0001, | |
| "dynamic_thresholding_ratio": 0.995, | |
| "euler_at_final": false, | |
| "final_sigmas_type": "zero", | |
| "flow_shift": 3.0, | |
| "lambda_min_clipped": -1000000.0, | |
| "lower_order_final": true, | |
| "num_train_timesteps": 1000, | |
| "prediction_type": "flow_prediction", | |
| "rescale_betas_zero_snr": false, | |
| "sample_max_value": 1.0, | |
| "solver_order": 3, | |
| "solver_type": "multistep", | |
| "steps_offset": 0, | |
| "thresholding": false, | |
| "timestep_spacing": "uniform_tau", | |
| "trained_betas": null, | |
| "use_beta_sigmas": false, | |
| "use_exponential_sigmas": false, | |
| "use_flow_sigmas": true, | |
| "use_karras_sigmas": false, | |
| "use_lu_lambdas": false, | |
| "apply_flow_shift": false, | |
| "variance_type": null, | |
| "update_clamp_factor": 2.5, | |
| "sigma_max": 1.0, | |
| "sigma_min": 0.002, | |
| "karras_rho": 7.0, | |
| "use_heun_final_steps": 3 | |
| } | |