Update README.md

README.md

@@ -1,3 +1,50 @@
 ---
 license: apache-2.0
+library_name: mlx-llm
+language:
+- en
+tags:
+- mlx
+- exbert
+datasets:
+- bookcorpus
+- wikipedia
 ---
+
+
+# BERT large model (uncased) - MLX 
+
+Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
+[this paper](https://arxiv.org/abs/1810.04805) and first released in
+[this repository](https://github.com/google-research/bert). This model is uncased: it does not make a difference
+between english and English.
+
+
+## Model description
+
+Please, refer to the [original model card](https://huggingface.co/bert-large-uncased) for more details on bert-base-uncased.
+
+## Use it with mlx-llm
+
+Install `mlx-llm` from GitHub.
+```bash
+git clone https://github.com/riccardomusmeci/mlx-llm
+cd mlx-llm
+pip install .
+```
+
+Run
+```python
+from mlx_llm.model import create_model
+from transformers import BertTokenizer
+import mlx.core as mx
+
+model = create_model("bert-large-uncased") # it will download weights from this repository
+tokenizer = BertTokenizer.from_pretrained("bert-large-uncased")
+
+batch = ["This is an example of BERT working on MLX."]
+tokens = tokenizer(batch, return_tensors="np", padding=True)
+tokens = {key: mx.array(v) for key, v in tokens.items()}
+
+output, pooled = model(**tokens)
+```