Text Generation
Transformers
Safetensors
GGUF
English
llama
tiny-model
from-scratch
model-growth
conversational
multi-turn
tool-use
agent-harness
retrieval-augmented
multi-hop-qa
question-answering
attribution
humble-ai
small-language-model
muon
text-generation-inference
Instructions to use textilelabs/Loom-Tapestry-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textilelabs/Loom-Tapestry-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="textilelabs/Loom-Tapestry-3") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("textilelabs/Loom-Tapestry-3") model = AutoModelForCausalLM.from_pretrained("textilelabs/Loom-Tapestry-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use textilelabs/Loom-Tapestry-3 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-Tapestry-3:F16 # Run inference directly in the terminal: llama cli -hf textilelabs/Loom-Tapestry-3:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf textilelabs/Loom-Tapestry-3:F16 # Run inference directly in the terminal: llama cli -hf textilelabs/Loom-Tapestry-3: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-Tapestry-3:F16 # Run inference directly in the terminal: ./llama-cli -hf textilelabs/Loom-Tapestry-3: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-Tapestry-3:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf textilelabs/Loom-Tapestry-3:F16
Use Docker
docker model run hf.co/textilelabs/Loom-Tapestry-3:F16
- LM Studio
- Jan
- vLLM
How to use textilelabs/Loom-Tapestry-3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "textilelabs/Loom-Tapestry-3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "textilelabs/Loom-Tapestry-3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/textilelabs/Loom-Tapestry-3:F16
- SGLang
How to use textilelabs/Loom-Tapestry-3 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 "textilelabs/Loom-Tapestry-3" \ --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": "textilelabs/Loom-Tapestry-3", "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 "textilelabs/Loom-Tapestry-3" \ --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": "textilelabs/Loom-Tapestry-3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use textilelabs/Loom-Tapestry-3 with Ollama:
ollama run hf.co/textilelabs/Loom-Tapestry-3:F16
- Unsloth Desktop
- Docker Model Runner
How to use textilelabs/Loom-Tapestry-3 with Docker Model Runner:
docker model run hf.co/textilelabs/Loom-Tapestry-3:F16
- Lemonade
How to use textilelabs/Loom-Tapestry-3 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull textilelabs/Loom-Tapestry-3:F16
Run and chat with the model
lemonade run user.Loom-Tapestry-3-F16
List all available models
lemonade list
- Atomic Chat
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99eb311 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | MIT License
Copyright (c) 2026 Textile Labs
Permission is hereby granted, free of charge, to any person obtaining a copy of this model
and associated files (the "Model"), to deal in the Model without restriction, including
without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
and/or sell copies of the Model, and to permit persons to whom the Model is furnished to do
so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or
substantial portions of the Model.
THE MODEL IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING
BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
CONNECTION WITH THE MODEL OR THE USE OR OTHER DEALINGS IN THE MODEL.
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