Update README.md

README.md

@@ -14,7 +14,7 @@ pipeline_tag: question-answering
 
 
 ## Model Details
- UlizaLlama7b-1 is a language model that builds upon the foundation of [Jacaranda/kiswallama-pretrained7B](https://huggingface.co/Jacaranda/kiswallama-pretrained). Jacaranda/kiswallama-pretrained is a large language model continually-pretrained with 321,530,045 swahili tokens and a customized tokenizer with  a swahili vocabulary of 20,000 tokens to extend the capabilities of [Meta/Llama2](https://huggingface.co/meta-llama/Llama-2-7b). It offers significant improvements in both encoding and decoding for Swahili text, surpassing the Swahili performance of Meta/Llama2. Moreover, Jacaranda/kiswallama-pretrained excels in providing accurate next-word completions in Swahili, a capability which  Meta/Llama2 falls short of. 
+ UlizaLlama is a 7B Parameters language model that builds upon the foundation of [Jacaranda/kiswallama-pretrained7B](https://huggingface.co/Jacaranda/kiswallama-pretrained). Jacaranda/kiswallama-pretrained is a large language model continually-pretrained with 321,530,045 swahili tokens and a customized tokenizer with  a swahili vocabulary of 20,000 tokens to extend the capabilities of [Meta/Llama2](https://huggingface.co/meta-llama/Llama-2-7b). It offers significant improvements in both encoding and decoding for Swahili text, surpassing the Swahili performance of Meta/Llama2. Moreover, Jacaranda/kiswallama-pretrained excels in providing accurate next-word completions in Swahili, a capability which  Meta/Llama2 falls short of. 
 ### Model Description
 - Origin: Adaptation of the Jacaranda/kiswallama-pretrained model.
 - Data: Instructional dataset in Swahili and English consisting of prompt-response pairs.
@@ -25,14 +25,14 @@ pipeline_tag: question-answering
 
 
 - **Developed by:** [Jacaranda Health](https://www.jacarandahealth.org/)
-- **Funded by [optional]:** [Google AI For Social Good Grant]
-- **Model type:** [LlamaModelForCausalLm]
-- **Language(s) (NLP):** [English and Swahili]
-- **License:** [to include]
-- **Model Developers:** [Stanslaus Mwongela, Jay Patel, Sathy Rajasekharan]
-- **Finetuned from model:** [ Jacaranda/kiswallama-pretrained model which builds upon Meta/Llama2]
+- **Funded by [optional]:** [Google.org](https://www.google.org/)
+- **Model type:** [LlamaModel](https://huggingface.co/models?other=llama)
+- **Language(s) (NLP):** Swahili and English
+- **License:** [CC BY-NC-SA 4.0 DEED](http://creativecommons.org/licenses/by-nc-sa/4.0/)
+- **Model Developers:** Stanslaus Mwongela, Jay Patel, Sathy Rajasekharan
+- **Finetuned from model:** [ Jacaranda/kiswallama-pretrained model](https://huggingface.co/Jacaranda/kiswallama-pretrained) which builds upon [Meta/Llama2](https://huggingface.co/meta-llama/Llama-2-7b)
 ## Uses
-UlizaLlama7b-1 is optimized for downstream tasks, notably those demanding instructional datasets in Swahili, English, or both. Organizations can further fine-tune it  for their specific domains. Potential areas include:
+UlizaLlama is optimized for downstream tasks, notably those demanding instructional datasets in Swahili, English, or both. Organizations can further fine-tune it  for their specific domains. Potential areas include:
 - Question-answering within specific domains.
 - Assistant-driven chat capabilities: healthcare, agriculture, legal, education, tourism and hospitality, public services, financial sectors, communication, customer assistance, commerce, etcpublic services, financial sectors, communication, customer assistance, commerce, etc.