Instructions to use Jershone/Echo-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Jershone/Echo-Mini with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Jershone/Echo-Mini",
	filename="Echo-Mini.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 Jershone/Echo-Mini with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Jershone/Echo-Mini
# Run inference directly in the terminal:
llama-cli -hf Jershone/Echo-Mini

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Jershone/Echo-Mini
# Run inference directly in the terminal:
llama-cli -hf Jershone/Echo-Mini

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 Jershone/Echo-Mini
# Run inference directly in the terminal:
./llama-cli -hf Jershone/Echo-Mini

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 Jershone/Echo-Mini
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Jershone/Echo-Mini

Use Docker

docker model run hf.co/Jershone/Echo-Mini

LM Studio
Jan

vLLM

How to use Jershone/Echo-Mini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Jershone/Echo-Mini"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Jershone/Echo-Mini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Jershone/Echo-Mini

Ollama
How to use Jershone/Echo-Mini with Ollama:
```
ollama run hf.co/Jershone/Echo-Mini
```

Unsloth Studio new

How to use Jershone/Echo-Mini 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 Jershone/Echo-Mini 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 Jershone/Echo-Mini to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Jershone/Echo-Mini to start chatting

Docker Model Runner
How to use Jershone/Echo-Mini with Docker Model Runner:
```
docker model run hf.co/Jershone/Echo-Mini
```

Lemonade

How to use Jershone/Echo-Mini with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Jershone/Echo-Mini

Run and chat with the model

lemonade run user.Echo-Mini-{{QUANT_TAG}}

List all available models

lemonade list

Jershone commited on 1 day ago

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Update README.md

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@@ -1,18 +1,17 @@
 ---
 license: apache-2.0
-base_model: MLM8372984732947/Echo-Mini
 tags:
-  - gguf
-  - text-generation
-  - edge-ai
-  - local-first
-  - micro-llm
-  - rag
 model_creator: MLM8372984732947
 model_name: Echo-Mini-22M-F16
 pipeline_tag: text-generation
 language:
-  - en
 ---
 # 🚀 Echo-Mini (22M Parameters - F16 GGUF)

 ---
 license: apache-2.0
 tags:
+- gguf
+- text-generation
+- edge-ai
+- local-first
+- micro-llm
+- rag
 model_creator: MLM8372984732947
 model_name: Echo-Mini-22M-F16
 pipeline_tag: text-generation
 language:
+- en
 ---
 # 🚀 Echo-Mini (22M Parameters - F16 GGUF)