Update README.md

README.md

@@ -50,7 +50,10 @@ It includes options for many training efficiency features such as [FlashAttentio
 
 ```python
 import transformers
-model = transformers.AutoModelForCausalLM.from_pretrained('mosaicml/mpt-7b-instruct', trust_remote_code=True)
+model = transformers.AutoModelForCausalLM.from_pretrained(
+  'mosaicml/mpt-7b-instruct',
+  trust_remote_code=True
+)
 ```
 Note: This model requires that `trust_remote_code=True` be passed to the `from_pretrained` method. 
 This is because we use a custom `MPT` model architecture that is not yet part of the Hugging Face `transformers` package.
@@ -58,19 +61,34 @@ This is because we use a custom `MPT` model architecture that is not yet part of
 
 To use the optimized [triton implementation](https://github.com/openai/triton) of FlashAttention, you can load the model with `attn_impl='triton'` and move the model to `bfloat16`:
 ```python
-config = transformers.AutoConfig.from_pretrained('mosaicml/mpt-7b-instruct', trust_remote_code=True)
+config = transformers.AutoConfig.from_pretrained(
+  'mosaicml/mpt-7b-instruct',
+  trust_remote_code=True
+)
 config.attn_config['attn_impl'] = 'triton'
 
-model = transformers.AutoModelForCausalLM.from_pretrained('mosaicml/mpt-7b-instruct', config=config, torch_dtype=torch.bfloat16, trust_remote_code=True)
+model = transformers.AutoModelForCausalLM.from_pretrained(
+  'mosaicml/mpt-7b-instruct',
+  config=config,
+  torch_dtype=torch.bfloat16,
+  trust_remote_code=True
+)
 model.to(device='cuda:0')
 ```
 
 Although the model was trained with a sequence length of 2048, ALiBi enables users to increase the maximum sequence length during finetuning and/or inference. For example:
 
 ```python
-config = transformers.AutoConfig.from_pretrained('mosaicml/mpt-7b', trust_remote_code=True)
+config = transformers.AutoConfig.from_pretrained(
+  'mosaicml/mpt-7b-instruct',
+  trust_remote_code=True
+)
 config.update({"max_seq_len": 4096})
-model = transformers.AutoModelForCausalLM.from_pretrained('mosaicml/mpt-7b', config=config, trust_remote_code=True)
+model = transformers.AutoModelForCausalLM.from_pretrained(
+  'mosaicml/mpt-7b-instruct',
+  config=config,
+  trust_remote_code=True
+)
 ```
 
 This model was trained with the [EleutherAI/gpt-neox-20b](https://huggingface.co/EleutherAI/gpt-neox-20b) tokenizer.