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, device_map="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 / configuration_fela.py

itstheraj

initial commit

309d916 21 days ago

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	from transformers import PretrainedConfig


	class FelaConfig(PretrainedConfig):
	model_type = "fela"

	def __init__(
	self,
	vocab_size=151936,
	seq_len=2048,
	n_layer=28,
	n_embd=1536,
	n_head=12,
	ffn_hidden=8960,
	layer_pattern="SSSL",
	gla_delta=True,
	fno_modes=512,
	gla_chunk=256,
	landmark_layer_every=7,
	landmark_chunk=32,
	landmark_max=64,
	attn_layer_every=0,
	tie_word_embeddings=False,
	use_cache=False,
	**kwargs,
	):
	self.vocab_size = vocab_size
	self.seq_len = seq_len
	self.n_layer = n_layer
	self.n_embd = n_embd
	self.n_head = n_head
	self.ffn_hidden = ffn_hidden
	self.layer_pattern = layer_pattern
	self.gla_delta = gla_delta
	self.fno_modes = fno_modes
	self.gla_chunk = gla_chunk
	self.landmark_layer_every = landmark_layer_every
	self.landmark_chunk = landmark_chunk
	self.landmark_max = landmark_max
	self.attn_layer_every = attn_layer_every
	self.num_hidden_layers = n_layer
	self.use_cache = use_cache
	super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)