Update transformers version in installation instructions

README.md

@@ -8,6 +8,16 @@ tags:
 datasets:
 - microsoft/Dayhoff
 ---
+---
+license: mit
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- protein-generation
+- jamba
+datasets:
+- microsoft/Dayhoff
+---
 
 # Model Card for Dayhoff
 
@@ -75,12 +85,12 @@ To import from HuggingFace, you will need to install these versions:
 
 ```bash
 uv pip install datasets==3.2.0 #for HF datasets
-uv pip install transformers==4.51.3
+uv pip install transformers==4.51.0
 uv pip install huggingface_hub~=0.34.4
  ```
 
 **Sample protein generation code:**
- 
+
 
 ```py
 
@@ -90,8 +100,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed
 set_seed(0)
 torch.set_default_device("cuda")
 
-model = AutoModelForCausalLM.from_pretrained('microsoft/Dayhoff-170m-GR')
-tokenizer = AutoTokenizer.from_pretrained('microsoft/Dayhoff-170m-GR', trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("microsoft/Dayhoff-3b-GR-HM-41000").to("cuda")
+tokenizer = AutoTokenizer.from_pretrained("microsoft/Dayhoff-3b-GR-HM-41000", trust_remote_code=True)
 
 
 inputs = tokenizer(tokenizer.bos_token, return_tensors="pt", return_token_type_ids=False)
@@ -253,4 +263,4 @@ The code and datasets released in this repository are provided for research and
 If you use the code, data, models, or results. please cite our [preprint](https://aka.ms/dayhoff/preprint).
 
 ## Data Summary
-https://huggingface.co/microsoft/Dayhoff-170m-GR/blob/main/data_summary_card.md
+https://huggingface.co/microsoft/Dayhoff-3b-GR-HM-41000/blob/main/data_summary_card.md