model-metadata/custom_code_execution_files

text stringlengths 0 759
pipe = pipeline("text-generation", model="tencent/Hunyuan-7B-Instruct")
File "/tmp/.cache/uv/environments-v2/4146d04fd154d95d/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 909, in pipeline
config = AutoConfig.from_pretrained(
model, _from_pipeline=task, code_revision=code_revision, hub_kwargs, model_kwargs
)
File "/tmp/.cache/uv/environments-v2/4146d04fd154d95d/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1273, in from_pretrained
raise ValueError(
...<8 lines>...
)
ValueError: The checkpoint you are trying to load has model type `hunyuan_v1_dense` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.

You can update Transformers with the command `pip install --upgrade transformers`. If this does not work, and the checkpoint is very new, then there may not be a release version that supports this model yet. In this case, you can get the most up-to-date code by installing Transformers from source with the command `pip install git+https://github.com/huggingface/transformers.git`
No suitable GPU found for tencent/Hunyuan-A13B-Instruct \| 389.33 GB VRAM requirement
No suitable GPU found for tencent/Hunyuan-A13B-Instruct \| 389.33 GB VRAM requirement
Traceback (most recent call last):
File "/tmp/tencent_POINTS-Reader_0zgiyoZ.py", line 13, in <module>
pipe = pipeline("image-text-to-text", model="tencent/POINTS-Reader", trust_remote_code=True)
File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1028, in pipeline
framework, model = infer_framework_load_model(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
adapter_path if adapter_path is not None else model,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
...<5 lines>...
**model_kwargs,
^^^^^^^^^^^^^^^
)
^
File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/base.py", line 333, in infer_framework_load_model
raise ValueError(
f"Could not load model {model} with any of the following classes: {class_tuple}. See the original errors:\n\n{error}\n"
)
ValueError: Could not load model tencent/POINTS-Reader with any of the following classes: (<class 'transformers.models.auto.modeling_auto.AutoModelForImageTextToText'>,). See the original errors:

while loading with AutoModelForImageTextToText, an error is thrown:
Traceback (most recent call last):
File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/base.py", line 293, in infer_framework_load_model
model = model_class.from_pretrained(model, **kwargs)
File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 607, in from_pretrained
raise ValueError(
...<2 lines>...
)
ValueError: Unrecognized configuration class <class 'transformers_modules.tencent.POINTS-Reader.42fbe5b5499fe3e30c275cbb00748eda22391621.configuration_pointsv15_chat.POINTSV15ChatConfig'> for this kind of AutoModel: AutoModelForImageTextToText.
Model type should be one of AriaConfig, AyaVisionConfig, BlipConfig, Blip2Config, ChameleonConfig, Cohere2VisionConfig, DeepseekVLConfig, DeepseekVLHybridConfig, Emu3Config, EvollaConfig, Florence2Config, FuyuConfig, Gemma3Config, Gemma3nConfig, GitConfig, Glm4vConfig, Glm4vMoeConfig, GotOcr2Config, IdeficsConfig, Idefics2Config, Idefics3Config, InstructBlipConfig, InternVLConfig, JanusConfig, Kosmos2Config, Kosmos2_5Config, Llama4Config, LlavaConfig, LlavaNextConfig, LlavaNextVideoConfig, LlavaOnevisionConfig, Mistral3Config, MllamaConfig, Ovis2Config, PaliGemmaConfig, PerceptionLMConfig, Pix2StructConfig, PixtralVisionConfig, Qwen2_5_VLConfig, Qwen2VLConfig, ShieldGemma2Config, SmolVLMConfig, UdopConfig, VipLlavaConfig, VisionEncoderDecoderConfig.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/base.py", line 311, in infer_framework_load_model
model = model_class.from_pretrained(model, **fp32_kwargs)
File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 607, in from_pretrained
raise ValueError(
...<2 lines>...
)
ValueError: Unrecognized configuration class <class 'transformers_modules.tencent.POINTS-Reader.42fbe5b5499fe3e30c275cbb00748eda22391621.configuration_pointsv15_chat.POINTSV15ChatConfig'> for this kind of AutoModel: AutoModelForImageTextToText.
Model type should be one of AriaConfig, AyaVisionConfig, BlipConfig, Blip2Config, ChameleonConfig, Cohere2VisionConfig, DeepseekVLConfig, DeepseekVLHybridConfig, Emu3Config, EvollaConfig, Florence2Config, FuyuConfig, Gemma3Config, Gemma3nConfig, GitConfig, Glm4vConfig, Glm4vMoeConfig, GotOcr2Config, IdeficsConfig, Idefics2Config, Idefics3Config, InstructBlipConfig, InternVLConfig, JanusConfig, Kosmos2Config, Kosmos2_5Config, Llama4Config, LlavaConfig, LlavaNextConfig, LlavaNextVideoConfig, LlavaOnevisionConfig, Mistral3Config, MllamaConfig, Ovis2Config, PaliGemmaConfig, PerceptionLMConfig, Pix2StructConfig, PixtralVisionConfig, Qwen2_5_VLConfig, Qwen2VLConfig, ShieldGemma2Config, SmolVLMConfig, UdopConfig, VipLlavaConfig, VisionEncoderDecoderConfig.



Traceback (most recent call last):
File "/tmp/tencent_POINTS-Reader_1bZPhuX.py", line 12, in <module>
model = AutoModelForCausalLM.from_pretrained("tencent/POINTS-Reader", trust_remote_code=True, torch_dtype="auto")
File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 586, in from_pretrained
model_class = get_class_from_dynamic_module(
class_ref, pretrained_model_name_or_path, code_revision=code_revision, hub_kwargs, kwargs
)
File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 569, in get_class_from_dynamic_module
final_module = get_cached_module_file(
repo_id,
...<8 lines>...
repo_type=repo_type,
)
File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 392, in get_cached_module_file
modules_needed = check_imports(resolved_module_file)
File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 224, in check_imports
raise ImportError(
...<2 lines>...
)
ImportError: This modeling file requires the following packages that were not found in your environment: PIL. Run `pip install PIL`
No suitable GPU found for tngtech/DeepSeek-TNG-R1T2-Chimera \| 3315.10 GB VRAM requirement
No suitable GPU found for tngtech/DeepSeek-TNG-R1T2-Chimera \| 3315.10 GB VRAM requirement
No suitable GPU found for trillionlabs/Tri-21B \| 100.37 GB VRAM requirement
No suitable GPU found for trillionlabs/Tri-21B \| 100.37 GB VRAM requirement
No suitable GPU found for trillionlabs/Tri-70B-preview-SFT \| 341.38 GB VRAM requirement
No suitable GPU found for trillionlabs/Tri-70B-preview-SFT \| 341.38 GB VRAM requirement
Traceback (most recent call last):
File "/tmp/vikhyatk_moondream2_0OEJSSq.py", line 13, in <module>
pipe = pipeline("image-text-to-text", model="vikhyatk/moondream2", trust_remote_code=True)
File "/tmp/.cache/uv/environments-v2/2a90239f0d4c576b/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 922, in pipeline
config = AutoConfig.from_pretrained(
model, _from_pipeline=task, code_revision=code_revision, hub_kwargs, model_kwargs
)
File "/tmp/.cache/uv/environments-v2/2a90239f0d4c576b/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1302, in from_pretrained
config_class = get_class_from_dynamic_module(
class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs
)
File "/tmp/.cache/uv/environments-v2/2a90239f0d4c576b/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 569, in get_class_from_dynamic_module
final_module = get_cached_module_file(
repo_id,
...<8 lines>...
repo_type=repo_type,

pipe = pipeline("text-generation", model="tencent/Hunyuan-7B-Instruct")

File "/tmp/.cache/uv/environments-v2/4146d04fd154d95d/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 909, in pipeline

config = AutoConfig.from_pretrained(

model, _from_pipeline=task, code_revision=code_revision, **hub_kwargs, **model_kwargs

)

File "/tmp/.cache/uv/environments-v2/4146d04fd154d95d/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1273, in from_pretrained

raise ValueError(

...<8 lines>...

)

ValueError: The checkpoint you are trying to load has model type `hunyuan_v1_dense` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.

You can update Transformers with the command `pip install --upgrade transformers`. If this does not work, and the checkpoint is very new, then there may not be a release version that supports this model yet. In this case, you can get the most up-to-date code by installing Transformers from source with the command `pip install git+https://github.com/huggingface/transformers.git`

No suitable GPU found for tencent/Hunyuan-A13B-Instruct | 389.33 GB VRAM requirement

Traceback (most recent call last):

File "/tmp/tencent_POINTS-Reader_0zgiyoZ.py", line 13, in <module>

pipe = pipeline("image-text-to-text", model="tencent/POINTS-Reader", trust_remote_code=True)

File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1028, in pipeline

framework, model = infer_framework_load_model(

~~~~~~~~~~~~~~~~~~~~~~~~~~^

adapter_path if adapter_path is not None else model,

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

...<5 lines>...

**model_kwargs,

^^^^^^^^^^^^^^^

)

^

File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/base.py", line 333, in infer_framework_load_model

raise ValueError(

f"Could not load model {model} with any of the following classes: {class_tuple}. See the original errors:\n\n{error}\n"

)

ValueError: Could not load model tencent/POINTS-Reader with any of the following classes: (<class 'transformers.models.auto.modeling_auto.AutoModelForImageTextToText'>,). See the original errors:

while loading with AutoModelForImageTextToText, an error is thrown:

Traceback (most recent call last):

File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/base.py", line 293, in infer_framework_load_model

model = model_class.from_pretrained(model, **kwargs)

File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 607, in from_pretrained

raise ValueError(

...<2 lines>...

)

ValueError: Unrecognized configuration class <class 'transformers_modules.tencent.POINTS-Reader.42fbe5b5499fe3e30c275cbb00748eda22391621.configuration_pointsv15_chat.POINTSV15ChatConfig'> for this kind of AutoModel: AutoModelForImageTextToText.

Model type should be one of AriaConfig, AyaVisionConfig, BlipConfig, Blip2Config, ChameleonConfig, Cohere2VisionConfig, DeepseekVLConfig, DeepseekVLHybridConfig, Emu3Config, EvollaConfig, Florence2Config, FuyuConfig, Gemma3Config, Gemma3nConfig, GitConfig, Glm4vConfig, Glm4vMoeConfig, GotOcr2Config, IdeficsConfig, Idefics2Config, Idefics3Config, InstructBlipConfig, InternVLConfig, JanusConfig, Kosmos2Config, Kosmos2_5Config, Llama4Config, LlavaConfig, LlavaNextConfig, LlavaNextVideoConfig, LlavaOnevisionConfig, Mistral3Config, MllamaConfig, Ovis2Config, PaliGemmaConfig, PerceptionLMConfig, Pix2StructConfig, PixtralVisionConfig, Qwen2_5_VLConfig, Qwen2VLConfig, ShieldGemma2Config, SmolVLMConfig, UdopConfig, VipLlavaConfig, VisionEncoderDecoderConfig.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):

File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/pipelines/base.py", line 311, in infer_framework_load_model

model = model_class.from_pretrained(model, **fp32_kwargs)

File "/tmp/.cache/uv/environments-v2/6770b8e53b9b72ed/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 607, in from_pretrained

raise ValueError(

...<2 lines>...

)

ValueError: Unrecognized configuration class <class 'transformers_modules.tencent.POINTS-Reader.42fbe5b5499fe3e30c275cbb00748eda22391621.configuration_pointsv15_chat.POINTSV15ChatConfig'> for this kind of AutoModel: AutoModelForImageTextToText.

Model type should be one of AriaConfig, AyaVisionConfig, BlipConfig, Blip2Config, ChameleonConfig, Cohere2VisionConfig, DeepseekVLConfig, DeepseekVLHybridConfig, Emu3Config, EvollaConfig, Florence2Config, FuyuConfig, Gemma3Config, Gemma3nConfig, GitConfig, Glm4vConfig, Glm4vMoeConfig, GotOcr2Config, IdeficsConfig, Idefics2Config, Idefics3Config, InstructBlipConfig, InternVLConfig, JanusConfig, Kosmos2Config, Kosmos2_5Config, Llama4Config, LlavaConfig, LlavaNextConfig, LlavaNextVideoConfig, LlavaOnevisionConfig, Mistral3Config, MllamaConfig, Ovis2Config, PaliGemmaConfig, PerceptionLMConfig, Pix2StructConfig, PixtralVisionConfig, Qwen2_5_VLConfig, Qwen2VLConfig, ShieldGemma2Config, SmolVLMConfig, UdopConfig, VipLlavaConfig, VisionEncoderDecoderConfig.

Traceback (most recent call last):

File "/tmp/tencent_POINTS-Reader_1bZPhuX.py", line 12, in <module>

model = AutoModelForCausalLM.from_pretrained("tencent/POINTS-Reader", trust_remote_code=True, torch_dtype="auto")

File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 586, in from_pretrained

model_class = get_class_from_dynamic_module(

class_ref, pretrained_model_name_or_path, code_revision=code_revision, **hub_kwargs, **kwargs

)

File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 569, in get_class_from_dynamic_module

final_module = get_cached_module_file(

repo_id,

...<8 lines>...

repo_type=repo_type,

)

File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 392, in get_cached_module_file

modules_needed = check_imports(resolved_module_file)

File "/tmp/.cache/uv/environments-v2/af8a44d08b0f1a72/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 224, in check_imports

raise ImportError(

...<2 lines>...

)

ImportError: This modeling file requires the following packages that were not found in your environment: PIL. Run `pip install PIL`

No suitable GPU found for tngtech/DeepSeek-TNG-R1T2-Chimera | 3315.10 GB VRAM requirement

No suitable GPU found for trillionlabs/Tri-21B | 100.37 GB VRAM requirement

No suitable GPU found for trillionlabs/Tri-70B-preview-SFT | 341.38 GB VRAM requirement

Traceback (most recent call last):

File "/tmp/vikhyatk_moondream2_0OEJSSq.py", line 13, in <module>

pipe = pipeline("image-text-to-text", model="vikhyatk/moondream2", trust_remote_code=True)

File "/tmp/.cache/uv/environments-v2/2a90239f0d4c576b/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 922, in pipeline

config = AutoConfig.from_pretrained(

model, _from_pipeline=task, code_revision=code_revision, **hub_kwargs, **model_kwargs

)

File "/tmp/.cache/uv/environments-v2/2a90239f0d4c576b/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1302, in from_pretrained

config_class = get_class_from_dynamic_module(

class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs

)

File "/tmp/.cache/uv/environments-v2/2a90239f0d4c576b/lib/python3.13/site-packages/transformers/dynamic_module_utils.py", line 569, in get_class_from_dynamic_module

final_module = get_cached_module_file(

repo_id,

...<8 lines>...

repo_type=repo_type,