Falcon-OCR on Linux/Transformers needs multiple compatibility fixes, not just eager attention

### 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:
- #3270 (MLX engine overrides for Apple Silicon)
- #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:

```python
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.:

```text
.../.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