Instructions to use voidful/llm-codec-abl-ftp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use voidful/llm-codec-abl-ftp with Transformers:

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

pipe = pipeline("text-generation", model="voidful/llm-codec-abl-ftp")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("voidful/llm-codec-abl-ftp")
model = AutoModelForCausalLM.from_pretrained("voidful/llm-codec-abl-ftp")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use voidful/llm-codec-abl-ftp with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "voidful/llm-codec-abl-ftp"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "voidful/llm-codec-abl-ftp",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/voidful/llm-codec-abl-ftp

SGLang

How to use voidful/llm-codec-abl-ftp 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 "voidful/llm-codec-abl-ftp" \
    --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": "voidful/llm-codec-abl-ftp",
		"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 "voidful/llm-codec-abl-ftp" \
        --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": "voidful/llm-codec-abl-ftp",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use voidful/llm-codec-abl-ftp with Docker Model Runner:
```
docker model run hf.co/voidful/llm-codec-abl-ftp
```

voidful commited on Mar 28

Commit

877af80

verified ·

1 Parent(s): f9a76f0

Upload ./llm-codec.pt with huggingface_hub

Browse files

Files changed (1) hide show

llm-codec.pt +2 -2

llm-codec.pt CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d1ec4dda922fc15afdb51a74d233f48dfa69472b959bd0bc59517dbcdbc5738c
-size 490847011

 version https://git-lfs.github.com/spec/v1
+oid sha256:851b7a46b7601ca2687630005177b71289e639fefa241be57b2f3cef5606f1dc
+size 490850507