update model name

README.md

@@ -12,9 +12,9 @@ metrics:
 pipeline_tag: text-generation
 ---
 
-# **Model Card for Basque Llama 7b**
+# **Model Card for Latxa 7b**
 
-Basque LLaMA is a collection of foundation models specifically tuned for Basque. Based on Meta’s LLaMA 2 model family, these models were further trained with Euscrawl, a highly curated Basque corpora ([Artetxe et al., 2022](https://aclanthology.org/2022.emnlp-main.499/)). Ranging from 7 billion to 70 billion parameters, these models are currently the biggest and best-performing LLMs built for Basque. This is the 7b repository, links to other models can be found in the index at the bottom.
+Latxa is a collection of foundation models specifically tuned for Basque. Based on Meta’s LLaMA 2 model family, these models were further trained with Euscrawl, a highly curated Basque corpora ([Artetxe et al., 2022](https://aclanthology.org/2022.emnlp-main.499/)). Ranging from 7 billion to 70 billion parameters, these models are currently the biggest and best-performing LLMs built for Basque. This is the 7b repository, links to other models can be found in the index at the bottom.
 
 
 # **Model Details**
@@ -22,7 +22,7 @@ Basque LLaMA is a collection of foundation models specifically tuned for Basque.
 
 ## **Model Description**
 
-Basque LLaMA is a family of Large Language Models (LLM) based on Meta’s [LLaMA models](https://huggingface.co/meta-llama). Current LLMs exhibit incredible performance for high-resource languages such as English, but, in the case of Basque and other low-resource languages, their performance is close to a random guesser. These limitations widen the gap between high- and low-resource languages when it comes to digital development. We present Basque LLaMA to overcome these limitations and promote the development of LLM-based technology and research for the Basque language. Basque LLaMA models follow the same architecture as their original counterparts and were further trained in Euscrawl v1 ([Artetxe et al., 2022](https://aclanthology.org/2022.emnlp-main.499/)), a high-quality Basque corpora. 
+Latxa is a family of Large Language Models (LLM) based on Meta’s [LLaMA models](https://huggingface.co/meta-llama). Current LLMs exhibit incredible performance for high-resource languages such as English, but, in the case of Basque and other low-resource languages, their performance is close to a random guesser. These limitations widen the gap between high- and low-resource languages when it comes to digital development. We present Latxa to overcome these limitations and promote the development of LLM-based technology and research for the Basque language. Latxa models follow the same architecture as their original counterparts and were further trained in Euscrawl v1 ([Artetxe et al., 2022](https://aclanthology.org/2022.emnlp-main.499/)), a high-quality Basque corpora. 
 
 The models are released in three sizes: 7B, 13B and 70B.
 
@@ -44,7 +44,7 @@ Use the code below to get started with the model.
 
 from transformers import pipeline
 
-pipe = pipeline("text-generation", model=”HiTZ/basque-llama-2-7b-v1”)
+pipe = pipeline("text-generation", model=”HiTZ/latxa-7b-v1”)
 
 text = "Euskara adimen artifizialera iritsi da!"
 
@@ -62,12 +62,12 @@ pipe(text, max_new_tokens=50, num_beams=5)
 
 # **Uses**
 
-Basque LLaMA models are intended to be used with Basque data; for any other language the performance is not guaranteed. Same as the original, Basque LLaMA inherits the [LLaMA-2 License](https://ai.meta.com/llama/license/) which allows for commercial and research use. 
+Latxa models are intended to be used with Basque data; for any other language the performance is not guaranteed. Same as the original, Latxa inherits the [LLaMA-2 License](https://ai.meta.com/llama/license/) which allows for commercial and research use. 
 
 
 ## **Direct Use**
 
-Basque LLaMA family models are pre-trained LLMs without any task-specific or instruction fine-tuning. That is, the model can either be prompted to perform a specific task or further fine-tuned for specific use cases.
+Latxa family models are pre-trained LLMs without any task-specific or instruction fine-tuning. That is, the model can either be prompted to perform a specific task or further fine-tuned for specific use cases.
 
 
 ## **Out-of-Scope Use**
@@ -77,7 +77,7 @@ The model was not fine-tuned to follow instructions or to work as a chat assista
 
 # **Bias, Risks, and Limitations**
 
-In an effort to alleviate the potentially disturbing or harmful content, Basque LLaMA has been trained on carefully selected and processed data which comes mainly from local media, national/regional newspapers, encyclopedias and blogs (see Euscrawl below). Still, the model is based on LLaMA models and can potentially carry the same bias, risk and limitations. 
+In an effort to alleviate the potentially disturbing or harmful content, Latxa has been trained on carefully selected and processed data which comes mainly from local media, national/regional newspapers, encyclopedias and blogs (see Euscrawl below). Still, the model is based on LLaMA models and can potentially carry the same bias, risk and limitations. 
 
 Please see the LLaMA’s _Ethical Considerations and Limitations _for further information.
 
@@ -115,7 +115,7 @@ The models were trained using the GPT-Neox library on the HPC CINECA computing c
    </td>
   </tr>
   <tr>
-   <td>Basque LLaMA 7B
+   <td>Latxa 7B
    </td>
    <td><p style="text-align: right">
 2000</p>
@@ -139,7 +139,7 @@ The models were trained using the GPT-Neox library on the HPC CINECA computing c
    </td>
   </tr>
   <tr>
-   <td>Basque LLaMA 13B
+   <td>Latxa 13B
    </td>
    <td><p style="text-align: right">
 1000</p>
@@ -163,7 +163,7 @@ The models were trained using the GPT-Neox library on the HPC CINECA computing c
    </td>
   </tr>
   <tr>
-   <td>Basque LLaMA 70B
+   <td>Latxa 70B
    </td>
    <td><p style="text-align: right">
 1680</p>
@@ -389,7 +389,7 @@ The model was evaluated using the LM Evaluation harness library from Eleuther AI
    </td>
   </tr>
   <tr>
-   <td><strong>Basque LLaMA 7B</strong>
+   <td><strong>Latxa 7B</strong>
    </td>
    <td>35.67
    </td>
@@ -411,7 +411,7 @@ The model was evaluated using the LM Evaluation harness library from Eleuther AI
    </td>
   </tr>
   <tr>
-   <td><strong>Basque LLaMA 13B</strong>
+   <td><strong>Latxa 13B</strong>
    </td>
    <td>53.56
    </td>
@@ -433,7 +433,7 @@ The model was evaluated using the LM Evaluation harness library from Eleuther AI
    </td>
   </tr>
   <tr>
-   <td><strong>Basque LLaMA 70B</strong>
+   <td><strong>Latxa 70B</strong>
    </td>
    <td><strong>71.78</strong>
    </td>