Instructions to use totoku/apex-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use totoku/apex-models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("totoku/apex-models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use totoku/apex-models 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 totoku/apex-models:Q4_K_M # Run inference directly in the terminal: llama cli -hf totoku/apex-models:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf totoku/apex-models:Q4_K_M # Run inference directly in the terminal: llama cli -hf totoku/apex-models: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 totoku/apex-models:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf totoku/apex-models: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 totoku/apex-models:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf totoku/apex-models:Q4_K_M
Use Docker
docker model run hf.co/totoku/apex-models:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use totoku/apex-models with Ollama:
ollama run hf.co/totoku/apex-models:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use totoku/apex-models with Docker Model Runner:
docker model run hf.co/totoku/apex-models:Q4_K_M
- Lemonade
How to use totoku/apex-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull totoku/apex-models:Q4_K_M
Run and chat with the model
lemonade run user.apex-models-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download HunyuanVideo-Foley/text_encoder/preprocessor_config.json from totoku/apex-models: direct link, hf CLI and curl.
- Browser
- Download file 541 Bytes
-
https://huggingface.co/totoku/apex-models/resolve/main/HunyuanVideo-Foley/text_encoder/preprocessor_config.json
- Command line
-
hf download hf://totoku/apex-models/HunyuanVideo-Foley/text_encoder/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/totoku/apex-models/resolve/main/HunyuanVideo-Foley/text_encoder/preprocessor_config.json
541 Bytes
| { | |
| "chunk_length_s": 10, | |
| "feature_extractor_type": "ClapFeatureExtractor", | |
| "feature_size": 64, | |
| "fft_window_size": 1024, | |
| "frequency_max": 14000, | |
| "frequency_min": 50, | |
| "hop_length": 480, | |
| "max_length_s": 10, | |
| "n_fft": 1024, | |
| "nb_frequency_bins": 513, | |
| "nb_max_frames": 1000, | |
| "nb_max_samples": 480000, | |
| "padding": "repeatpad", | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "ClapProcessor", | |
| "return_attention_mask": false, | |
| "sampling_rate": 48000, | |
| "top_db": null, | |
| "truncation": "rand_trunc" | |
| } | |