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fix bug in speedrun script, batch size that doesn't OOM on 8XH100 for d24 is 16
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@ -69,13 +69,10 @@ python -m scripts.tok_eval
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echo "Waiting for dataset download to complete..."
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wait $DATASET_DOWNLOAD_PID
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# Number of processes/GPUs to use
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NPROC_PER_NODE=8
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# d24 model (slightly overtrained is enough to beat GPT-2 => increase data:params ratio from compute optimal 10.5 (default) to 12)
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torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.base_train -- --depth=24 --target-param-data-ratio=12 --run=$WANDB_RUN
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torchrun --standalone --nproc_per_node=8 -m scripts.base_train -- --depth=24 --target-param-data-ratio=12 --device-batch-size=16 --run=$WANDB_RUN
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# evaluate the model: CORE metric, BPB on train/val, and draw samples
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torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.base_eval
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torchrun --standalone --nproc_per_node=8 -m scripts.base_eval -- --device-batch-size=16
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# -----------------------------------------------------------------------------
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# SFT (teach the model conversation special tokens, tool use, multiple choice)
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@ -85,8 +82,8 @@ torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.base_eval
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curl -L -o $NANOCHAT_BASE_DIR/identity_conversations.jsonl https://karpathy-public.s3.us-west-2.amazonaws.com/identity_conversations.jsonl
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# run SFT and eval the model
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torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.chat_sft -- --run=$WANDB_RUN
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torchrun --standalone --nproc_per_node=$NPROC_PER_NODE -m scripts.chat_eval -- -i sft
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torchrun --standalone --nproc_per_node=8 -m scripts.chat_sft -- --device-batch-size=16 --run=$WANDB_RUN
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torchrun --standalone --nproc_per_node=8 -m scripts.chat_eval -- -i sft
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# chat with the model over CLI! Leave out the -p to chat interactively
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# python -m scripts.chat_cli -p "Why is the sky blue?"
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