Update README.md

README.md

@@ -3,15 +3,17 @@ pipeline_tag: text-generation
 inference: false
 license: apache-2.0
 datasets:
-  - public-qiskit
-  - synthetic-qiskit
+- public-qiskit
+- synthetic-qiskit
 metrics:
-  - code_eval
+- code_eval
 library_name: transformers
 tags:
-  - code
-  - granite
-  - qiskit
+- code
+- granite
+- qiskit
+base_model:
+- ibm-granite/granite-3.3-8b-instruct
 ---
 
 # granite-3.3-8b-qiskit
@@ -77,4 +79,4 @@ We train granite-3.3-8b-qiskit using IBM's super computing cluster (Vela) using
 
 ## Ethical Considerations and Limitations
 
-The use of Large Language Models involves risks and ethical considerations people must be aware of. Regarding code generation, caution is urged against complete reliance on specific code models for crucial decisions or impactful information as the generated code is not guaranteed to work as intended. **granite-3.3-8b-qiskit** model is not the exception in this regard. Even though this model is suited for multiple code-related tasks, it has not undergone any safety alignment, there it may produce problematic outputs. Additionally, it remains uncertain whether smaller models might exhibit increased susceptibility to hallucination in generation scenarios by copying source code verbatim from the training dataset due to their reduced sizes and memorization capacities. This aspect is currently an active area of research, and we anticipate more rigorous exploration, comprehension, and mitigations in this domain. Regarding ethics, a latent risk associated with all Large Language Models is their malicious utilization. We urge the community to use **granite-3.3-8b-qiskit** model with ethical intentions and in a responsible way.
+The use of Large Language Models involves risks and ethical considerations people must be aware of. Regarding code generation, caution is urged against complete reliance on specific code models for crucial decisions or impactful information as the generated code is not guaranteed to work as intended. **granite-3.3-8b-qiskit** model is not the exception in this regard. Even though this model is suited for multiple code-related tasks, it has not undergone any safety alignment, there it may produce problematic outputs. Additionally, it remains uncertain whether smaller models might exhibit increased susceptibility to hallucination in generation scenarios by copying source code verbatim from the training dataset due to their reduced sizes and memorization capacities. This aspect is currently an active area of research, and we anticipate more rigorous exploration, comprehension, and mitigations in this domain. Regarding ethics, a latent risk associated with all Large Language Models is their malicious utilization. We urge the community to use **granite-3.3-8b-qiskit** model with ethical intentions and in a responsible way.