![]() ![]() ![]() I tried to mildly modify both transformers/convert_pytorch_checkpoint_to_tf2.py and transformers/commands/pt_to_tf.py and take a chance either of them would work. I'm trying to mitigate this by adopting tensorflow-metal (by Apple) which presumably be more polished on macOS, however couldn't find an easy way to convert bloom pt back to tensorflow checkpoints. Support for APFS-snapshot enabled volumesĪPFS volumes that contain snapshots are automatically detected and mounted in read-only mode.Hi I'm trying to infer bloom on my apple silicon Mac (20c 128G), however model runs extremely slow on CPU (60s/layer, seemingly not properly parallelized) nor mps backend working properly (outputs identical token for various inputs, 0.1s/layer though). Our driver can only work with APFS containers residing on a single physical store, other configurations are not yet supported. Our driver supports all of them.Īny operations that involve file moving from one APFS subvolume to another are not supported. There are several compression methods in APFS. You can read, copy and rename this type of files, but not write, modify, create or delete. Our driver provides limited read-only support for APFS cloned files. However, this feature can be disabled at any moment in the program interface. Mounts supported volumes automatically at startup, so you don’t need to bother about it each time you restart the operating system or power your computer on. When volumes are mounted in the Write mode, you get full access to an APFS volume with the options to edit files, create new files or delete existing files. Thrifty usage of processor, memory, and disk resources Steady throughput and balanced goodput with effective flow control, reduced overheads, and congestion avoidance Protection of data integrity and prevention of accidental data corruption and possible loss
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