Update README.md

README.md

@@ -15,13 +15,13 @@ metrics:
 - comet
 pipeline_tag: translation
 ---
-# Model Card for TowerInstruct-7B-v0.1
+# Model Card for TowerInstruct-7B-v0.2
 
 ## Model Details
 
 ### Model Description
 
-TowerInstruct-7B is a language model that results from fine-tuning TowerBase on the TowerBlocks supervised fine-tuning dataset. TowerInstruct-7B-v0.1 is the first model in the series. 
+TowerInstruct-7B is a language model that results from fine-tuning TowerBase on the TowerBlocks supervised fine-tuning dataset. TowerInstruct-7B-v0.2 is the first model in the series. 
 The model is trained to handle several translation-related tasks, such as general machine translation (e.g., sentence- and paragraph/document-level translation, terminology-aware translation, context-aware translation), automatic post edition, named-entity recognition, gramatical error correction, and paraphrase generation. 
 We will release more details in the upcoming technical report.
 
@@ -31,7 +31,7 @@ We will release more details in the upcoming technical report.
 - **License:** CC-BY-NC-4.0, Llama 2 is licensed under the [LLAMA 2 Community License](https://ai.meta.com/llama/license/), Copyright © Meta Platforms, Inc. All Rights Reserved.
 - **Finetuned from model:** [TowerBase](https://huggingface.co/Unbabel/TowerBase-7B-v0.1)
 
-**Update**: TowerInstruct-7B-v0.2 has more reliable document-level translation capabilities in comparison with TowerInstruct-7B-v0.1. The new version of TowerBlocks used to train v0.2 is also available in the Tower collection. 
+**Update**: TowerInstruct-7B-v0.2 has more reliable document-level translation capabilities in comparison with TowerInstruct-7B-v0.2. The new version of TowerBlocks used to train v0.2 is also available in the Tower collection. 
 
 ## Intended uses & limitations
 
@@ -59,7 +59,7 @@ Here's how you can run the model using the `pipeline()` function from 🤗 Trans
 import torch
 from transformers import pipeline
 
-pipe = pipeline("text-generation", model="Unbabel/TowerInstruct-v0.1", torch_dtype=torch.bfloat16, device_map="auto")
+pipe = pipeline("text-generation", model="Unbabel/TowerInstruct-v0.2", torch_dtype=torch.bfloat16, device_map="auto")
 # We use the tokenizer’s chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
 messages = [
     {"role": "user", "content": "Translate the following text from Portuguese into English.\nPortuguese: Um grupo de investigadores lançou um novo modelo para tarefas relacionadas com tradução.\nEnglish:"},
@@ -82,11 +82,11 @@ We are currently working on improving quality and consistency on document-level
 
 ## Bias, Risks, and Limitations
 
-TowerInstruct-v0.1 has not been aligned to human preferences, so the model may generate problematic outputs (e.g., hallucinations, harmful content, or false statements).  
+TowerInstruct-v0.2 has not been aligned to human preferences, so the model may generate problematic outputs (e.g., hallucinations, harmful content, or false statements).  
 
 ## Prompt Format
 
-TowerInstruct-v0.1 was trained using the ChatML prompt templates without any system prompts. An example follows below:
+TowerInstruct-v0.2 was trained using the ChatML prompt templates without any system prompts. An example follows below:
 ```
 <|im_start|>user
 {USER PROMPT}<|im_end|>