Instructions to use totoku/apex-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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]

llama-cpp-python

How to use totoku/apex-models with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="totoku/apex-models",
	filename="Chroma1-HD/text_encoder/text_encoder-q8_0.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use totoku/apex-models with llama.cpp:

Install from brew

brew install llama.cpp
# 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

Install from WinGet (Windows)

winget install llama.cpp
# 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

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 Studio new

How to use totoku/apex-models 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 totoku/apex-models 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 totoku/apex-models to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for totoku/apex-models to start chatting

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

totoku commited on Feb 8

Commit

3bca448

verified ·

1 Parent(s): e3bb644

Create config.json

Browse files

Files changed (1) hide show

Wan2.2-I2V/low_noise_transformer/config.json +25 -0

Wan2.2-I2V/low_noise_transformer/config.json ADDED Viewed

	@@ -0,0 +1,25 @@

+{
+    "_class_name": "WanTransformer3DModel",
+    "_diffusers_version": "0.35.0.dev0",
+    "added_kv_proj_dim": null,
+    "attention_head_dim": 128,
+    "cross_attn_norm": true,
+    "eps": 1e-06,
+    "ffn_dim": 13824,
+    "freq_dim": 256,
+    "image_dim": null,
+    "in_channels": 36,
+    "num_attention_heads": 40,
+    "num_layers": 40,
+    "out_channels": 16,
+    "patch_size": [
+      1,
+      2,
+      2
+    ],
+    "pos_embed_seq_len": null,
+    "qk_norm": "rms_norm_across_heads",
+    "rope_max_seq_len": 1024,
+    "text_dim": 4096
+  }