diff --git a/README.md b/README.md
index 5f69ad778f..dd093ebaec 100644
--- a/README.md
+++ b/README.md
@@ -13,7 +13,7 @@ The library currently contains PyTorch implementations, pre-trained model weight
 5. **[XLNet](https://github.com/zihangdai/xlnet/)** (from Google/CMU) released with the paper [​XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237) by Zhilin Yang*, Zihang Dai*, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le.
 6. **[XLM](https://github.com/facebookresearch/XLM/)** (from Facebook) released together with the paper [Cross-lingual Language Model Pretraining](https://arxiv.org/abs/1901.07291) by Guillaume Lample and Alexis Conneau.
 7. **[RoBERTa](https://github.com/pytorch/fairseq/tree/master/examples/roberta)** (from Facebook), released together with the paper a [Robustly Optimized BERT Pretraining Approach](https://arxiv.org/abs/1907.11692) by Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov.
-8. **[DistilBERT](https://github.com/huggingface/pytorch-transformers/tree/master/examples/distillation)** (from HuggingFace), released together with the blogpost [Smaller, faster, cheaper, lighter: Introducing DistilBERT, a distilled version of BERT](https://medium.com/huggingface/smaller-faster-cheaper-lighter-introducing-distilbert-a-distilled-version-of-bert-8cf3380435b5
+8. **[DistilBERT](https://github.com/huggingface/pytorch-transformers/tree/master/examples/distillation)** (from HuggingFace), released together with the blogpost [Smaller, faster, cheaper, lighter: Introducing DistilBERT, a distilled version of BERT](https://medium.com/huggingface/distilbert-8cf3380435b5
 ) by Victor Sanh, Lysandre Debut and Thomas Wolf.
 
 These implementations have been tested on several datasets (see the example scripts) and should match the performances of the original implementations (e.g. ~93 F1 on SQuAD for BERT Whole-Word-Masking, ~88 F1 on RocStories for OpenAI GPT, ~18.3 perplexity on WikiText 103 for Transformer-XL, ~0.916 Peason R coefficient on STS-B for XLNet). You can find more details on the performances in the Examples section of the [documentation](https://huggingface.co/pytorch-transformers/examples.html).
diff --git a/docs/source/pretrained_models.rst b/docs/source/pretrained_models.rst
index 2bbb7ae7a1..af7702ad5d 100644
--- a/docs/source/pretrained_models.rst
+++ b/docs/source/pretrained_models.rst
@@ -113,11 +113,11 @@ Here is the full list of the currently provided pretrained models together with
 +-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
 | DistilBERT        | ``distilbert-base-uncased``                                | | 6-layer, 768-hidden, 12-heads, 66M parameters                                                                                       |
 |                   |                                                            | | The DistilBERT model distilled from the BERT model `bert-base-uncased` checkpoint                                                   |
-|                   |                                                            | (see `details <https://medium.com/@victorsanh/8cf3380435b5>`__)                                                                       |
+|                   |                                                            | (see `details <https://medium.com/huggingface/distilbert-8cf3380435b5>`__)                                                                       |
 |                   +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
 |                   | ``distilbert-base-uncased-distilled-squad``                | | 6-layer, 768-hidden, 12-heads, 66M parameters                                                                                       |
 |                   |                                                            | | The DistilBERT model distilled from the BERT model `bert-base-uncased` checkpoint, with an additional linear layer.                 |
-|                   |                                                            | (see `details <https://medium.com/@victorsanh/8cf3380435b5>`__)                                                                       |
+|                   |                                                            | (see `details <https://medium.com/huggingface/distilbert-8cf3380435b5>`__)                                                                       |
 +-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
 
 .. <https://huggingface.co/pytorch-transformers/examples.html>`__
\ No newline at end of file
diff --git a/pytorch_transformers/modeling_distilbert.py b/pytorch_transformers/modeling_distilbert.py
index 6ae18bdb01..4a0f3a101b 100644
--- a/pytorch_transformers/modeling_distilbert.py
+++ b/pytorch_transformers/modeling_distilbert.py
@@ -440,7 +440,7 @@ DISTILBERT_START_DOCSTRING = r"""
     `detailed blog post`_
     
     .. _`detailed blog post`:
-        https://medium.com/huggingface/smaller-faster-cheaper-lighter-introducing-distilbert-a-distilled-version-of-bert-8cf3380435b5
+        https://medium.com/huggingface/distilbert-8cf3380435b5
 
     Parameters:
         config (:class:`~pytorch_transformers.DistilBertConfig`): Model configuration class with all the parameters of the model.