Bug

On the Linux TransformersVlmEngine path, the falcon_ocr preset currently needs a small bundle of Falcon-specific compatibility fixes. Forcing eager attention is necessary, but it is not sufficient on its own.

This appears to be separate from:

• Add MLX engine overrides for falcon_ocr, lightonocr, glm_ocr VLM presets #3270 (MLX engine overrides for Apple Silicon)
• VlmPipeline TransformersVlmEngine breaks on transformers v5 for AUTOMODEL_CAUSALLM models (TokenizersBackend has no attribute 'tokenizer') #3273 (Transformers v5 tokenizer alias issue for TokenizersBackend)

Inference is local. The failures happen while loading and running the local model through Transformers with trust_remote_code=True.

Steps to reproduce

On Linux, with a Docling setup that resolves falcon_ocr to the Transformers engine:

from docling.datamodel.base_models import InputFormat
from docling.datamodel.pipeline_options import VlmConvertOptions, VlmPipelineOptions
from docling.document_converter import DocumentConverter, PdfFormatOption
from docling.pipeline.vlm_pipeline import VlmPipeline

vlm_options = VlmConvertOptions.from_preset("falcon_ocr")
pipeline_options = VlmPipelineOptions(
    vlm_options=vlm_options,
    allow_external_plugins=True,
    enable_remote_services=True,
)
converter = DocumentConverter(
    format_options={
        InputFormat.PDF: PdfFormatOption(
            pipeline_cls=VlmPipeline,
            pipeline_options=pipeline_options,
        )
    }
)
converter.convert("sample.pdf")

Actual behavior

On the Linux/Transformers path we hit a sequence of Falcon-specific failures:

• attention backend dispatch: Falcon-OCR does not support SDPA yet, so the model must be loaded with public attn_implementation="eager"
• config initialization: the eager setting must be present on the actual Falcon config object used for model init, not just inferred later
• generation config loading: the Falcon repo does not ship generation_config.json, so GenerationConfig.from_model_config(...) fallback is needed
• prompt formatting: Falcon does not ship a usable chat template for the generic Transformers VLM path
• inference path: Falcon's remote-code model needs to use its native OCR generation entrypoints instead of Docling's generic chat-template processor flow

Relevant stack shape:

• docling.models.inference_engines.vlm.factory.create_vlm_engine
• AutoInlineVlmEngine
• TransformersVlmEngine
• model_cls.from_pretrained(...)
• FalconOCRForCausalLM

The underlying module is loaded from the HF cache, e.g.:

.../.cache/huggingface/modules/transformers_modules/.../modeling_falcon_ocr.py

Expected behavior

falcon_ocr should initialize and run successfully on Linux when Docling routes it through the Transformers engine.

Suggested fix direction

Docling should treat Falcon-OCR as a small Transformers compatibility special case on the Linux path:

• honor explicit public attn_implementation overrides
• default Falcon-OCR to eager attention on the Transformers preset
• preload the Falcon config with eager attention before model construction
• fall back when generation_config.json is missing
• bypass the generic chat-template prompt path and use Falcon's native OCR generation flow

Status

Tracked in #3279.

Docling version

2.86.0

Python version

3.13.13

Additional environment details

• transformers==5.5.3
• observed on Linux CUDA path
• Apple Silicon MLX path is not affected because it avoids the Transformers engine for this preset