Instructions to use textilelabs/Loom-Router-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use textilelabs/Loom-Router-1 with Transformers:

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

pipe = pipeline("text-classification", model="textilelabs/Loom-Router-1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("textilelabs/Loom-Router-1")
model = AutoModelForCausalLM.from_pretrained("textilelabs/Loom-Router-1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use textilelabs/Loom-Router-1 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 textilelabs/Loom-Router-1:F16
# Run inference directly in the terminal:
llama cli -hf textilelabs/Loom-Router-1:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf textilelabs/Loom-Router-1:F16
# Run inference directly in the terminal:
llama cli -hf textilelabs/Loom-Router-1:F16

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 textilelabs/Loom-Router-1:F16
# Run inference directly in the terminal:
./llama-cli -hf textilelabs/Loom-Router-1:F16

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 textilelabs/Loom-Router-1:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf textilelabs/Loom-Router-1:F16

Use Docker

docker model run hf.co/textilelabs/Loom-Router-1:F16

LM Studio
Jan
Ollama
How to use textilelabs/Loom-Router-1 with Ollama:
```
ollama run hf.co/textilelabs/Loom-Router-1:F16
```
Unsloth Desktop
Docker Model Runner
How to use textilelabs/Loom-Router-1 with Docker Model Runner:
```
docker model run hf.co/textilelabs/Loom-Router-1:F16
```

Lemonade

How to use textilelabs/Loom-Router-1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull textilelabs/Loom-Router-1:F16

Run and chat with the model

lemonade run user.Loom-Router-1-F16

List all available models

lemonade list

Atomic Chat

Loom-Router-1

File size: 875 Bytes

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# Training data attribution

Loom Router 1 was trained on utterances from two openly licensed corpora. Both
licences require attribution; this file satisfies that requirement and must be
kept with any redistribution.

## MASSIVE — CC BY 4.0
Amazon. "MASSIVE: A 1M-Example Multilingual Natural Language Understanding
Dataset with 51 Typologically-Diverse Languages."
https://github.com/alexa/massive — licensed CC BY 4.0.
MASSIVE is derived from SLURP, also licensed CC BY 4.0.

## CLINC150 — CC BY 3.0
Larson et al. "An Evaluation Dataset for Intent Classification and Out-of-Scope
Prediction." https://github.com/clinc/oos-eval — licensed CC BY 3.0.

Only the English portions were used. Intent labels were remapped onto the 17
Loom routes; no utterance text was altered except for surface augmentation
(casing, punctuation, filler) applied to training copies only.