Update README.md

README.md

@@ -7,7 +7,7 @@ language:
 inference: false
 ---
 
-# MosaicBERT: mosaic-bert-base-seqlen-512 Pretrained Model 
+# MosaicBERT: mosaic-bert-base-seqlen-256 Pretrained Model 
 
 MosaicBERT-Base is a new BERT architecture and training recipe optimized for fast pretraining. 
 MosaicBERT trains faster and achieves higher pretraining and finetuning accuracy when benchmarked against 
@@ -42,7 +42,7 @@ April 2023
 
 ```python
 from transformers import AutoModelForMaskedLM
-mlm = AutoModelForMaskedLM.from_pretrained('mosaicml/mosaic-bert-base', trust_remote_code=True)
+mlm = AutoModelForMaskedLM.from_pretrained('mosaicml/mosaic-bert-base-seqlen-256', trust_remote_code=True)
 ```
 
 The tokenizer for this model is simply the Hugging Face `bert-base-uncased` tokenizer.
@@ -58,7 +58,7 @@ To use this model directly for masked language modeling, use `pipeline`:
 from transformers import AutoModelForMaskedLM, BertTokenizer, pipeline
 
 tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
-mlm = AutoModelForMaskedLM.from_pretrained('mosaicml/mosaic-bert-base', trust_remote_code=True)
+mlm = AutoModelForMaskedLM.from_pretrained('mosaicml/mosaic-bert-base-seqlen-256', trust_remote_code=True)
 
 classifier = pipeline('fill-mask', model=mlm, tokenizer=tokenizer)
 
@@ -75,7 +75,7 @@ This model requires that `trust_remote_code=True` be passed to the `from_pretrai
 
 ```python
 mlm = AutoModelForMaskedLM.from_pretrained(
-   'mosaicml/mosaic-bert-base',
+   'mosaicml/mosaic-bert-base-seqlen-256',
    trust_remote_code=True,
    revision='24512df',
 )