Update README.md

README.md

@@ -35,13 +35,13 @@ This is a fine-tuned version of the **Gemma-2-2B-IT** model, aimed at helping us
 <!-- - **License:** [More Information Needed] -->
 - **Finetuned from model [optional]:** [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it)
 
-### Model Sources [optional]
+### Model Sources 
 
 <!-- Provide the basic links for the model. -->
 
 - **Repository:** [gemma-2-2b-it-ThinkLink](https://huggingface.co/MinnieMin/gemma-2-2b-it-ThinkLink)
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+<!-- - **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed] -->
 
 ## Uses
 
@@ -54,7 +54,7 @@ This is a fine-tuned version of the **Gemma-2-2B-IT** model, aimed at helping us
 This model can be used for educational purposes, especially for coding test preparation. It generates step-by-step problem-solving hints and structured questions to guide users through coding problems.
 
 
-### Downstream Use [optional]
+### Downstream Use 
 
 <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
@@ -68,11 +68,11 @@ This model can be used for educational purposes, especially for coding test prep
 - Direct code generation without understanding the steps may lead to incorrect or misleading results.
 - It is not suitable for tasks that require a detailed and immediate answer to general-purpose questions or advanced mathematical computations.
 
-## Bias, Risks, and Limitations
+<!-- ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+This section is meant to convey both technical and sociotechnical limitations.
 
-[More Information Needed]
+[More Information Needed] -->
 
 ### Recommendations
 
@@ -115,87 +115,47 @@ The model was fine-tuned on a dataset of structured coding test problems and sol
 - Fine-tuning approach: Low-Rank Adaptation (LoRA)
 
 
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+<!-- #### Training Hyperparameters
 
 #### Speeds, Sizes, Times [optional]
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+This section provides information about throughput, start/end time, checkpoint size if relevant, etc.
 
 [More Information Needed]
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+This section describes the evaluation protocols and provides the results.
 
 ### Testing Data, Factors & Metrics
 
 #### Testing Data
 
-<!-- This should link to a Dataset Card if possible. -->
+This should link to a Dataset Card if possible.
 
 [More Information Needed]
 
 #### Factors
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+These are the things the evaluation is disaggregating by, e.g., subpopulations or domains.
 
 [More Information Needed]
 
 #### Metrics
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
+These are the evaluation metrics being used, ideally with a description of why.
 
 [More Information Needed]
 
 ### Results
 
-[More Information Needed]
+[More Information Needed] -->
 
 #### Summary
 The model was able to effectively guide users through various coding challenges by providing structured hints and questions that promoted deeper understanding.
 
 
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
+## Citation 
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
@@ -206,26 +166,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
   title = {ThinkLink Gemma-2-2B-IT: A Guided Problem-Solving Model},
   year = {2024},
   url = {https://huggingface.co/MinnieMin/gemma-2-2b-it-ThinkLink},
-}
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+}