Add hindi and turkish examples for generate

README.md

@@ -115,7 +115,7 @@ metrics:
 
 <img src="aya-fig1.png" alt="Aya model summary image" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
 
-# Model Card for Aya Model
+# Model Card for Aya 101
 
 ## Model Summary
 
@@ -128,7 +128,7 @@ metrics:
 - **Developed by:** Cohere For AI
 - **Model type:** a Transformer style autoregressive massively multilingual language model.
 - **Paper**: [Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model](arxiv.com)
-- **Point of Contact**: [Ahmet Ustun](mailto:ahmet@cohere.com)
+- **Point of Contact**: Cohere For AI: [cohere.for.ai](cohere.for.ai)
 - **Languages**: Refer to the list of languages in the `language` section of this model card.
 - **License**: Apache-2.0
 - **Model**: [Aya](https://huggingface.co/CohereForAI/aya)
@@ -141,22 +141,31 @@ metrics:
 # pip install -q transformers
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
-checkpoint = "CohereForAI/aya_model"
+checkpoint = "CohereForAI/aya-101"
 
 tokenizer = AutoTokenizer.from_pretrained(checkpoint)
 aya_model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
 
-inputs = tokenizer.encode("Translate to English: Je t’aime.", return_tensors="pt")
-outputs = aya_model.generate(inputs)
-print(tokenizer.decode(outputs[0]))
+# Turkish to English translation
+tur_inputs = tokenizer.encode("Translate to English: Aya cok dilli bir dil modelidir.", return_tensors="pt")
+tur_outputs = aya_model.generate(inputs, max_new_tokens=128)
+print(tokenizer.decode(tur_outputs[0]))
+# Aya is a multi-lingual language model
+
+# Q: Why are there so many languages in India?
+hin_inputs = tokenizer.encode("भारत में इतनी सारी भाषाएँ क्यों हैं?", return_tensors="pt")
+hin_outputs = aya_model.generate(inputs, max_new_tokens=128)
+print(tokenizer.decode(hin_outputs[0]))
+# Expected output: भारत में कई भाषाएँ हैं और विभिन्न भाषाओं के बोली जाने वाले लोग हैं। यह विभिन्नता भाषाई विविधता और सांस्कृतिक विविधता का परिणाम है। Translates to "India has many languages and people speaking different languages. This diversity is the result of linguistic diversity and cultural diversity."
+
 ```
 
 ## Model Details
 
-### Training
+### Finetuning
 
 - Architecture: Same as [mt5-xxl](https://huggingface.co/google/mt5-xxl)
-- Number of Finetuning Samples: 25M
+- Number of Samples seen during Finetuning: 25M
 - Batch size: 256
 - Hardware: TPUv4-128
 - Software: T5X, Jax
@@ -190,15 +199,13 @@ We hope that the release of the Aya model will make community-based redteaming e
 
 ```
 @article{,
-  title={},
-  author={},
+  title={Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model},
+  author={Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, Wei-Yin Ko, Daniel D'souza, Gbemileke Onilude, Neel Bhandari, Shivalika Singh, Hui-Lee Ooi, Amr Kayid, Freddie Vargus, Phil Blunsom, Shayne Longpre, Niklas Muennighoff, Marzieh Fadaee, Julia Kreutzer, Sara Hooker},
   journal={Preprint},
   year={2024}
 }
 ```
 
-**APA:**
-
 ## Languages Covered
 
 Below is the list of languages used in finetuning the Aya Model. We group languages into higher-, mid-, and lower-resourcedness based on a language classification by [Joshi et. al, 2020](https://microsoft.github.io/linguisticdiversity/). For further details, refer to our [paper]()