Upload LiquidAI_LFM2.5-VL-1.6B_0.txt with huggingface_hub

LiquidAI_LFM2.5-VL-1.6B_0.txt

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+```CODE: 
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("image-text-to-text", model="LiquidAI/LFM2.5-VL-1.6B")
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
+            {"type": "text", "text": "What animal is on the candy?"}
+        ]
+    },
+]
+pipe(text=messages)
+```
+
+ERROR: 
+Traceback (most recent call last):
+  File "/tmp/LiquidAI_LFM2.5-VL-1.6B_0UdM7pr.py", line 26, in <module>
+    pipe = pipeline("image-text-to-text", model="LiquidAI/LFM2.5-VL-1.6B")
+  File "/tmp/.cache/uv/environments-v2/0145a12032cf2475/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1197, in pipeline
+    raise e
+  File "/tmp/.cache/uv/environments-v2/0145a12032cf2475/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1188, in pipeline
+    processor = AutoProcessor.from_pretrained(processor, _from_pipeline=task, **hub_kwargs, **model_kwargs)
+  File "/tmp/.cache/uv/environments-v2/0145a12032cf2475/lib/python3.13/site-packages/transformers/models/auto/processing_auto.py", line 396, in from_pretrained
+    return processor_class.from_pretrained(
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        pretrained_model_name_or_path, trust_remote_code=trust_remote_code, **kwargs
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/0145a12032cf2475/lib/python3.13/site-packages/transformers/processing_utils.py", line 1394, in from_pretrained
+    args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/0145a12032cf2475/lib/python3.13/site-packages/transformers/processing_utils.py", line 1453, in _get_arguments_from_pretrained
+    args.append(attribute_class.from_pretrained(pretrained_model_name_or_path, **kwargs))
+                ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/0145a12032cf2475/lib/python3.13/site-packages/transformers/models/auto/tokenization_auto.py", line 1153, in from_pretrained
+    raise ValueError(
+        f"Tokenizer class {tokenizer_class_candidate} does not exist or is not currently imported."
+    )
+ValueError: Tokenizer class TokenizersBackend does not exist or is not currently imported.