Update README.md

README.md

@@ -23,9 +23,9 @@ The final distribution of documents by topic is shown in the chart below:
 ## Model details
 
 The models were trained for one epoch on sequences of 4096 tokens. During training, we used many modern optimizations such as:
-- [torch.compile](pytorch.org/docs/stable/generated/torch.compile.html)
+- [torch.compile](https://pytorch.org/docs/stable/generated/torch.compile.html)
 - [adamw_apex_fused](https://huggingface.co/docs/transformers/main/en/perf_train_gpu_one#optimizer-choice) optimizer
-- [Flash Attention 2](github.com/Dao-AILab/flash-attention)
+- [Flash Attention 2](https://github.com/Dao-AILab/flash-attention)
 - [Mixed precision](https://huggingface.co/docs/transformers/main/en/perf_train_gpu_one#bf16) (`--bf16` and `--tf32` options)
 - [Gradient accumulation](https://huggingface.co/docs/transformers/main/en/perf_train_gpu_one#gradient-accumulation)
 - [Fully Sharded Data Parallel (FSDP)](https://pytorch.org/tutorials/intermediate/FSDP_tutorial.html) with the SHARD_GRAD_OP mode