
* feat: adding new vlm-models support Signed-off-by: Peter Staar <taa@zurich.ibm.com> * fixed the transformers Signed-off-by: Peter Staar <taa@zurich.ibm.com> * got microsoft/Phi-4-multimodal-instruct to work Signed-off-by: Peter Staar <taa@zurich.ibm.com> * working on vlm's Signed-off-by: Peter Staar <taa@zurich.ibm.com> * refactoring the VLM part Signed-off-by: Peter Staar <taa@zurich.ibm.com> * all working, now serious refacgtoring necessary Signed-off-by: Peter Staar <taa@zurich.ibm.com> * refactoring the download_model Signed-off-by: Peter Staar <taa@zurich.ibm.com> * added the formulate_prompt Signed-off-by: Peter Staar <taa@zurich.ibm.com> * pixtral 12b runs via MLX and native transformers Signed-off-by: Peter Staar <taa@zurich.ibm.com> * added the VlmPredictionToken Signed-off-by: Peter Staar <taa@zurich.ibm.com> * refactoring minimal_vlm_pipeline Signed-off-by: Peter Staar <taa@zurich.ibm.com> * fixed the MyPy Signed-off-by: Peter Staar <taa@zurich.ibm.com> * added pipeline_model_specializations file Signed-off-by: Peter Staar <taa@zurich.ibm.com> * need to get Phi4 working again ... Signed-off-by: Peter Staar <taa@zurich.ibm.com> * finalising last points for vlms support Signed-off-by: Peter Staar <taa@zurich.ibm.com> * fixed the pipeline for Phi4 Signed-off-by: Peter Staar <taa@zurich.ibm.com> * streamlining all code Signed-off-by: Peter Staar <taa@zurich.ibm.com> * reformatted the code Signed-off-by: Peter Staar <taa@zurich.ibm.com> * fixing the tests Signed-off-by: Peter Staar <taa@zurich.ibm.com> * added the html backend to the VLM pipeline Signed-off-by: Peter Staar <taa@zurich.ibm.com> * fixed the static load_from_doctags Signed-off-by: Peter Staar <taa@zurich.ibm.com> * restore stable imports Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * use AutoModelForVision2Seq for Pixtral and review example (including rename) Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * remove unused value Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * refactor instances of VLM models Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * skip compare example in CI Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * use lowercase and uppercase only Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * add new minimal_vlm example and refactor pipeline_options_vlm_model for cleaner import Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * rename pipeline_vlm_model_spec Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * move more argument to options and simplify model init Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * add supported_devices Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * remove not-needed function Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * exclude minimal_vlm Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * missing file Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * add message for transformers version Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * rename to specs Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * use module import and remove MLX from non-darwin Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * remove hf_vlm_model and add extra_generation_args Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * use single HF VLM model class Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * remove torch type Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * add docs for vision models Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> --------- Signed-off-by: Peter Staar <taa@zurich.ibm.com> Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
41 lines
984 B
Python
41 lines
984 B
Python
import logging
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from pathlib import Path
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from typing import Optional
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_log = logging.getLogger(__name__)
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def download_hf_model(
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repo_id: str,
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local_dir: Optional[Path] = None,
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force: bool = False,
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progress: bool = False,
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revision: Optional[str] = None,
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) -> Path:
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from huggingface_hub import snapshot_download
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from huggingface_hub.utils import disable_progress_bars
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if not progress:
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disable_progress_bars()
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download_path = snapshot_download(
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repo_id=repo_id,
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force_download=force,
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local_dir=local_dir,
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revision=revision,
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)
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return Path(download_path)
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class HuggingFaceModelDownloadMixin:
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@staticmethod
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def download_models(
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repo_id: str,
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local_dir: Optional[Path] = None,
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force: bool = False,
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progress: bool = False,
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) -> Path:
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return download_hf_model(
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repo_id=repo_id, local_dir=local_dir, force=force, progress=progress
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)
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