Instructions to use Infinix-io/humanizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Infinix-io/humanizer with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Infinix-io/humanizer")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Infinix-io/humanizer")
model = AutoModelForMultimodalLM.from_pretrained("Infinix-io/humanizer", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Infinix-io/humanizer 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 Infinix-io/humanizer:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Infinix-io/humanizer:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Infinix-io/humanizer:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Infinix-io/humanizer: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 Infinix-io/humanizer:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Infinix-io/humanizer: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 Infinix-io/humanizer:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Infinix-io/humanizer:Q4_K_M

Use Docker

docker model run hf.co/Infinix-io/humanizer:Q4_K_M

LM Studio
Jan

vLLM

How to use Infinix-io/humanizer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Infinix-io/humanizer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Infinix-io/humanizer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Infinix-io/humanizer:Q4_K_M

SGLang

How to use Infinix-io/humanizer with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Infinix-io/humanizer" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Infinix-io/humanizer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Infinix-io/humanizer" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Infinix-io/humanizer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Infinix-io/humanizer with Ollama:
```
ollama run hf.co/Infinix-io/humanizer:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use Infinix-io/humanizer with Docker Model Runner:
```
docker model run hf.co/Infinix-io/humanizer:Q4_K_M
```

Lemonade

How to use Infinix-io/humanizer with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Infinix-io/humanizer:Q4_K_M

Run and chat with the model

lemonade run user.humanizer-Q4_K_M

List all available models

lemonade list

Atomic Chat

humanizer

File size: 1,535 Bytes

da49358

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  "audio_token": "<|audio|>",
  "backend": "tokenizers",
  "boa_token": "<|audio>",
  "boi_token": "<|image>",
  "bos_token": "<bos>",
  "eoa_token": "<audio|>",
  "eoc_token": "<channel|>",
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  "local_files_only": false,
  "mask_token": "<mask>",
  "model_max_length": 1000000000000000019884624838656,
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  "pad_token": "<pad>",
  "padding_side": "left",
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}