Instructions to use lowdown-labs/fela-autocomplete with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lowdown-labs/fela-autocomplete with Transformers:

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

pipe = pipeline("text-generation", model="lowdown-labs/fela-autocomplete", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("lowdown-labs/fela-autocomplete", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use lowdown-labs/fela-autocomplete with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/lowdown-labs/fela-autocomplete

SGLang

How to use lowdown-labs/fela-autocomplete 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 "lowdown-labs/fela-autocomplete" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lowdown-labs/fela-autocomplete",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "lowdown-labs/fela-autocomplete" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lowdown-labs/fela-autocomplete",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use lowdown-labs/fela-autocomplete with Docker Model Runner:
```
docker model run hf.co/lowdown-labs/fela-autocomplete
```

fela-autocomplete / space /README.md

itstheraj

initial commit

309d916 6 days ago

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	---
	title: FELA LLM 1.5 code completion
	colorFrom: indigo
	colorTo: purple
	sdk: gradio
	sdk_version: 4.44.0
	app_file: app.py
	pinned: false
	license: other
	---

	# FELA LLM 1.5 code completion

	Type the code before your cursor (Prefix) and optionally the code after it (Suffix), and
	the model writes the line that goes in between. It runs on a plain CPU with no GPU.

	## How it works

	The model reads your prefix and suffix, and when the suffix is present it uses the fill
	in the middle layout so the completion fits between them. It writes one line at a time,
	greedy by default, so the same prompt gives the same real output every time.

	## What to expect

	This is the final fill in the middle model. Single line patterns land well (imports,
	obvious returns, boilerplate); multi line blocks and novel logic are outside what it is
	built for. Every completion is a genuine forward of the model, never a lookup. For fast
	production serving the same weights run int8 on the CPU native FELA server.