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from hi-ml.
Related Issues (20)
- Fine-tuning for Radiology Report Generation HOT 1
- Pretraining/training script, loss functions for hi-ml-multimodal (BioViL) HOT 1
- Environment variables are not passed through when using the SDK v2 codepath HOT 1
- Pass an entire command to ScriptRunConfig instead of script path and arguments
- Submitting to AML with `health_azure` removes the trailing line from `.amlignore`
- Submitting a job to a compute instance fails because the number of nodes can't be read
- Reproducing RSNA Pneumonia zero-shot results
- `_download_file_from_run` silently does nothing if `is_local_rank_zero()` returns `False`
- Please fix "pip install hi-ml-multimodal" or use my fork for a working version HOT 5
- Hyperdrive config arguments ignored silently when the `entry_command` is specified
- SDKv2 Runs - `aml_workspace` ignored, error message and documentation could be improved.
- Potential performance issue: Unreliable performance of .loc in pandas 2.0.3
- Pretrained model for BioVIL HOT 2
- Unable to install hi-ml, and pytorch and torchvision could not find a version that satisfies the requirement (torch==1.9.0 torchvision==0.10.0) HOT 9
- Warning from Huggingface when using hi-ml-multimodal HOT 2
- Reproducing zero-shot temporal image classification results on the MS-CXR-T benchmark
- Finetuning on report generation task HOT 2
- How to fine-tune with my own data HOT 1
- Update model code on HuggingFace HOT 6
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from hi-ml.