Superduper allows users to work with self-hosted LLM models via [vLLM](https://github.com/vllm-project/vllm).
Project description
superduper_vllm
Superduper allows users to work with self-hosted LLM models via vLLM.
Installation
pip install superduper_vllm
API
Class | Description |
---|---|
superduper_vllm.model.VllmChat |
VLLM model for chatting. |
superduper_vllm.model.VllmCompletion |
VLLM model for generating completions. |
Examples
VllmChat
from superduper_vllm import VllmChat
vllm_params = dict(
model="hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
quantization="awq",
dtype="auto",
max_model_len=1024,
tensor_parallel_size=1,
)
model = VllmChat(identifier="model", vllm_params=vllm_params)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "hello"},
]
Chat with chat format messages
model.predict(messages)
Chat with text format messages
model.predict("hello")
VllmCompletion
from superduper_vllm import VllmCompletion
vllm_params = dict(
model="hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
quantization="awq",
dtype="auto",
max_model_len=1024,
tensor_parallel_size=1,
)
model = VllmCompletion(identifier="model", vllm_params=vllm_params)
model.predict("hello")
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
superduper_vllm-0.0.5.tar.gz
(13.9 kB
view details)
Built Distribution
File details
Details for the file superduper_vllm-0.0.5.tar.gz
.
File metadata
- Download URL: superduper_vllm-0.0.5.tar.gz
- Upload date:
- Size: 13.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c16517c5dc18337aca71f1e35b609b6e5f0e90b19fa76f9f98d24ad73ff46754 |
|
MD5 | a78e5860637469d3f8e893217d425b2a |
|
BLAKE2b-256 | 8c41d4522e7993d41a04cbee948b3c420d0fdde64bdf1fd7c9664ae7eea736b3 |
File details
Details for the file superduper_vllm-0.0.5-py3-none-any.whl
.
File metadata
- Download URL: superduper_vllm-0.0.5-py3-none-any.whl
- Upload date:
- Size: 12.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f264a4d57023861040825e3be1fdbae119a51c81f8c0bd34fd4db49fc0594ac0 |
|
MD5 | 25bf4147108ba36c1ab2874eb56ddadc |
|
BLAKE2b-256 | e96815490af39964a06b67bea725e800a0d349455bd10cf7c3282eb427fa4413 |