Update README.md

README.md

@@ -9,8 +9,8 @@ pipeline_tag: text-generation
 
 ## Description
 
-This is a **transformer-decoder** [gpt2 model](https://huggingface.co/gpt2), adapted for **single turn dialogue tasks**. We fine-tuned a 345M parameters [DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium) model from Microsoft, following the CLM (Causal Language Modelling) objective.
-We used one of the datasets available in the [Bot Framework Tools repository](https://github.com/microsoft/botframework-cli). We processed [the professional-styled personality chat dataset in Spanish](https://github.com/microsoft/botframework-cli/blob/main/packages/qnamaker/docs/chit-chat-dataset.md), the file is available [here](https://qnamakerstore.blob.core.windows.net/qnamakerdata/editorial/spanish/qna_chitchat_professional.tsv)
+This is a **transformer-decoder** [GPT-2 model](https://huggingface.co/gpt2), adapted for **single-turn dialogue tasks in Spanish**. We fine-tuned a [DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium) 345M parameters model from Microsoft, following the CLM (Causal Language Modelling) objective.
+We used one of the datasets available in the [Bot Framework Tools repository](https://github.com/microsoft/botframework-cli). We processed [the professional-styled personality chat dataset in Spanish](https://github.com/microsoft/botframework-cli/blob/main/packages/qnamaker/docs/chit-chat-dataset.md), the file is available [here to download](https://qnamakerstore.blob.core.windows.net/qnamakerdata/editorial/spanish/qna_chitchat_professional.tsv)
 
 ---
 
@@ -23,7 +23,7 @@ import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 CHAT_TURNS = 5
-MAX_LENGTH=1000
+MAX_LENGTH = 1000
 
 model = AutoModelForCausalLM.from_pretrained('ITG/DialoGPT-medium-spanish-chitchat')
 tokenizer = AutoTokenizer.from_pretrained('ITG/DialoGPT-medium-spanish-chitchat')
@@ -40,9 +40,7 @@ for i in range(CHAT_TURNS):
     # decode just the last generated output tokens from the model (do not include the user prompt again)
     step_model_answer = tokenizer.decode(chat_history[:, user_inputs_ids.shape[-1]:][0], skip_special_tokens=True)
   print(f"Step - {i} >> DialoGPT-spanish model answer -> {step_model_answer}")
-
 ```
-
 ---
 
 ## Examples
@@ -68,13 +66,13 @@ for i in range(CHAT_TURNS):
 
 ---
 
-## Fine-tuning in different dataset
+## Fine-tuning in a different dataset or style
 
 If you want to fine-tune this model, we recommend you to start from the [DialoGPT model](https://huggingface.co/microsoft/DialoGPT-medium).
 You can check the [original GitHub repository](https://github.com/microsoft/DialoGPT).
 
 ## Limitations
 
-- This model is intended to be used **just for single-turn chitchat conversations in Spanish**
-- This model's generation capabilities are limited to the extent of the aforementioned fine-tuning dataset
-- This model generates short answers, providing general context dialogue in a professional style
+- This model is intended to be used **just for single-turn chitchat conversations in Spanish**.
+- This model's generation capabilities are limited to the extent of the aforementioned fine-tuning dataset.
+- This model generates short answers, providing general context dialogue in a professional style.