Instructions to use TobDeBer/myContainers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TobDeBer/myContainers with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="TobDeBer/myContainers",
	filename="arco_BE8.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use TobDeBer/myContainers 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 TobDeBer/myContainers
# Run inference directly in the terminal:
llama cli -hf TobDeBer/myContainers

Install from WinGet (Windows)

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

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 TobDeBer/myContainers
# Run inference directly in the terminal:
./llama-cli -hf TobDeBer/myContainers

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 TobDeBer/myContainers
# Run inference directly in the terminal:
./build/bin/llama-cli -hf TobDeBer/myContainers

Use Docker

docker model run hf.co/TobDeBer/myContainers

LM Studio
Jan
Ollama
How to use TobDeBer/myContainers with Ollama:
```
ollama run hf.co/TobDeBer/myContainers
```

Unsloth Studio

How to use TobDeBer/myContainers 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 TobDeBer/myContainers 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 TobDeBer/myContainers to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for TobDeBer/myContainers to start chatting

Atomic Chat new
Docker Model Runner
How to use TobDeBer/myContainers with Docker Model Runner:
```
docker model run hf.co/TobDeBer/myContainers
```

Lemonade

How to use TobDeBer/myContainers with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull TobDeBer/myContainers

Run and chat with the model

lemonade run user.myContainers-{{QUANT_TAG}}

List all available models

lemonade list

myContainers / assistant.patch

TobDeBer

assistant patches

4d0c2cb almost 2 years ago

Raw

History Blame Contribute Delete

2.36 kB

	diff --git a/examples/server/public/index-new.html b/examples/server/public/index-new.html
	index c87dd8f1..d1aed025 100644
	--- a/examples/server/public/index-new.html
	+++ b/examples/server/public/index-new.html
	@@ -1063,7 +1063,7 @@ return html`
	return html`
	<div class="mode-${session.value.type}">
	<header>
	- <h2>llama.cpp</h2>
	+ <h2>modelname</h2>
	<div class="dropdown">
	<button class="dropbtn"><svg width="16" height="16" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><circle cx="12" cy="12" r="10" stroke-width="2"/></svg></button>
	<div class="dropdown-content" id="theme-selector">
	diff --git a/examples/server/public/index.html b/examples/server/public/index.html
	index 07fec6a3..0d873f3f 100644
	--- a/examples/server/public/index.html
	+++ b/examples/server/public/index.html
	@@ -3,7 +3,7 @@
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1" />
	<meta name="color-scheme" content="light dark">
	- <title>llama.cpp - chat</title>
	+ <title>assistantname - chat</title>

	<style>
	body {
	@@ -288,12 +288,12 @@
	var slot_id = -1;

	const session = signal({
	- prompt: "This is a conversation between User and Llama, a friendly chatbot. Llama is helpful, kind, honest, good at writing, and never fails to answer any requests immediately and with precision.",
	+ prompt: "This is a conversation between User and assistantname, a friendly chatbot. assistantname is helpful, kind, honest, good at writing, and never fails to answer any requests immediately and with precision.",
	template: "{{prompt}}\n\n{{history}}\n{{char}}:",
	historyTemplate: "{{name}}: {{message}}",
	transcript: [],
	type: "chat", // "chat" \| "completion"
	- char: "Llama",
	+ char: "assistantname",
	user: "User",
	image_selected: ''
	})
	@@ -1258,7 +1258,7 @@
	<header>
	<div class="grid-container">
	<div class="grid-item"></div>
	- <div class="grid-item"><h1>llama.cpp</h1></div>
	+ <div class="grid-item"><h1>modelname</h1></div>
	<div class="grid-item"><a class="customlink" href="index-new.html">New UI</a></div>
	</div>
	</header>