Add support for batched generation

README.md

@@ -4,15 +4,43 @@ This is a replica of Alpaca by Stanford' tatsu
 
 Trained using the original instructions with a minor modification in FSDP mode
 
-# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
-
-| Metric                | Value                     |
-|-----------------------|---------------------------|
-| Avg.                  | 41.96   |
-| ARC (25-shot)         | 52.3          |
-| HellaSwag (10-shot)   | 77.09    |
-| MMLU (5-shot)         | 41.6         |
-| TruthfulQA (0-shot)   | 37.58   |
-| Winogrande (5-shot)   | 69.46   |
-| GSM8K (5-shot)        | 1.44        |
-| DROP (3-shot)         | 14.23         |
+# Other versions:
+13B: https://huggingface.co/chavinlo/alpaca-13b
+
+13B -> GPT4 : https://huggingface.co/chavinlo/gpt4-x-alpaca
+
+## Compute Used
+Trained on 4xA100s for 6H
+Donated by redmond.ai
+
+NO LORA HAS BEEN USED, this is a natively-finetuned model, hence "alpaca-native"
+
+If you are interested on more llama-based models, you can check out my profile or search for other models at https://huggingface.co/models?other=llama
+
+This (MIGHT) be a quantized version of this model, but be careful: https://boards.4channel.org/g/thread/92173062#p92182396
+
+CONFIGURATION (default except fsdp):
+
+```shell
+torchrun --nproc_per_node=4 --master_port=3045 train.py \
+    --model_name_or_path /workspace/llama-7b-hf \
+    --data_path ./alpaca_data.json \
+    --bf16 True \
+    --output_dir /workspace/output \
+    --num_train_epochs 3 \
+    --per_device_train_batch_size 4 \
+    --per_device_eval_batch_size 4 \
+    --gradient_accumulation_steps 8 \
+    --evaluation_strategy "no" \
+    --save_strategy "steps" \
+    --save_steps 200 \
+    --save_total_limit 1 \
+    --learning_rate 2e-5 \
+    --weight_decay 0. \
+    --warmup_ratio 0.03 \
+    --lr_scheduler_type "cosine" \
+    --logging_steps 1 \
+    --fsdp "shard_grad_op auto_wrap" \
+    --fsdp_transformer_layer_cls_to_wrap 'LLaMADecoderLayer' \
+    --tf32 True --report_to="wandb"
+```