Custom guided decoding backend specifications To launch the custom guided decoding backend you must provide the name of a directory that contains a single backend.py file and any other *.whl Python wheel files that are required as additional dependencies, including transitive dependencies, not already...
guided_decoding_backend: str): completion = await client.completions.create( model=MODEL_NAME, prompt=f"Give an example JSON for an employee profile " f"that fits this schema: {TEST_SCHEMA}", n=3, temperature=1.0, max_tokens=500, extra_body=dict(guided_json=TEST_SCHEMA)) extra_body=dic...
int, int]], engine_args: AsyncEngineArgs, n: int, guided_decoding: bool = False, warmup: bool = False, disable_frontend_multiprocessing: bool = False, ) -> float: from vllm import SamplingParams async with build_async_engine_client_from_engine_args( engine_args, disable_frontend_multipro...
To launch the custom guided decoding backend you must provide the name of a directory that contains a singlebackend.pyfile and any other*.whlPython wheel files that are required as additional dependencies, including transitive dependencies, not already included in NIM. The directory structure should ...
A high-throughput and memory-efficient inference and serving engine for LLMs - Revert "[Misc][Bugfix] Disable guided decoding for mistral tokenizer"…· vllm-project/vllm@02c9afa
I would suggest trying out setting --guided-decoding-backend lm-format-enforcer (through args) or "guided_decoding_backend": "lm-format-enforcer" as part of the request to see whether it helps. see original PR here: #3868 (cc @noamgat) Contributor noamgat commented May 7, 2024 If te...
def test_mistral_guided_decoding( vllm_runner, model: str, guided_backend: str, ) -> None: with vllm_runner(model, dtype='bfloat16', tokenizer_mode="mistral") as vllm_model: guided_decoding = GuidedDecodingParams(json=SAMPLE_JSON_SCHEMA, backend=guided_backend) params = SamplingParams(...
@stikkireddy your code should run now, if you switch the guided_decoding_backend to lm-format-enforcer from vllm import LLM llm = LLM( model="/root/models/mistralai/Pixtral-12B-2409", tokenizer_mode="mistral", served_model_name="mistralai/Pixtral-12B-2409", max_model_len=5*4096, gui...
🚀 The feature, motivation and pitch Currently we support guided decoding of (JSON, Regex, Choice, Grammar, and arbitrary JSON) in OpenAI inference server. It would be great that we expose the same functionality in the offline interface a...
feat: support spectulative decoding grammar advances c791187 Collaborator Author drbh commented Feb 14, 2024 Nice :) Have you verified if it works well with speculation? Now it should 🙂 fix: add disable_grammar_support to docker_launcher args 12c7aae Collaborator Author drbh commented Fe...