Model Failing when using HuggingFace pipeline

[saptarshi059]

Hi,

So I've been trying to use very basic text generation inference with this model using HuggingFace's pipeline API. However, it keeps on crashing when trying to generate sequences with max_tokens = 10000

from transformers import pipeline generator = pipeline('text-generation', model = 'facebook/galactica-125m', device=0) generator('covid-19', renormalize_logits=True, do_sample=True, max_new_tokens=10000)[0]['generated_text']

I updated my Transformers and Torch libraries. CUDA version = 11.7 | torch = 1.14.0 (nightly) [Stable also was not working] | transformers = 4.25.1

GPUs = NVIDIA A100

Error: RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling cublasLtMatmul( ltHandle, computeDesc.descriptor(), &alpha_val, mat1_ptr, Adesc.descriptor(), mat2_ptr, Bdesc.descriptor(), &beta_val, result_ptr, Cdesc.descriptor(), result_ptr, Cdesc.descriptor(), &heuristicResult.algo, workspace.data_ptr(), workspaceSize, at::cuda::getCurrentCUDAStream())

[mkardas]

Hi @saptarshi059, all the models were trained with context window of 2048 tokens. Does the above code work if you set max_new_tokens=100?

[cvinker]

@mkardas This explains the errors I have been getting, I am assuming one's meant to program it to be able to write longer, perhaps making it run in a loop with a portion of the previous output as its prompt.

[mkardas]

Yes, this kind of moving window approach should work, but is not provided out of the box.

[saptarshi059]

@mkardas Oh I see. Thank you so much. Yes, it does work with max_new_tokens < 2048. I will try the moving window approach then.