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Update sft_lora_finetune_llm.mdx #765

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14 changes: 7 additions & 7 deletions docs/source/training_tutorials/sft_lora_finetune_llm.mdx
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Expand Up @@ -50,6 +50,11 @@ huggingface-cli login --token YOUR_TOKEN
```bash
git clone https://github.com/huggingface/optimum-neuron.git
```
5. Install trl using:
```bash
pip install trl==0.11.4
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We now do this with the extra "training" see here:

optimum-neuron/docs/source/training_tutorials/sft_lora_finetune_llm.mdx

Line 61 in e84e0c6

python -m pip install .[training]

```


## 2. Load and prepare the dataset

Expand Down Expand Up @@ -230,13 +235,8 @@ BS=1
GRADIENT_ACCUMULATION_STEPS=8
LOGGING_STEPS=1
MODEL_NAME="meta-llama/Meta-Llama-3-8B"
OUTPUT_DIR=output-$SLURM_JOB_ID
OUTPUT_DIR=dolly_llama

if [ "$NEURON_EXTRACT_GRAPHS_ONLY" = "1" ]; then
MAX_STEPS=$((LOGGING_STEPS + 5))
else
MAX_STEPS=-1
fi


XLA_USE_BF16=1 neuron_parallel_compile torchrun --nproc_per_node $PROCESSES_PER_NODE docs/source/training_tutorials/sft_lora_finetune_llm.py \
Expand All @@ -245,7 +245,7 @@ XLA_USE_BF16=1 neuron_parallel_compile torchrun --nproc_per_node $PROCESSES_PER_
--do_train \
--learning_rate 5e-5 \
--warmup_ratio 0.03 \
--max_steps $MAX_STEPS \
--max_steps 11 \ #changed max_steps to 11 so that it can have enough cycles to run
--per_device_train_batch_size $BS \
--per_device_eval_batch_size $BS \
--gradient_accumulation_steps $GRADIENT_ACCUMULATION_STEPS \
Expand Down