Update README.md

README.md

@@ -4,61 +4,36 @@ language:
 - en
 pipeline_tag: text-generation
 ---
-
-# Model Card for Model ID
-
 <!-- Provide a quick summary of what the model is/does. -->
 
-Model finetuned with knowledge distillation specifically for expertise on AMD technologies and python coding.
-
-## Model Details
+Finetuned Llama 3.2 Instruct model with knowledge distillation  
+specifically for expertise on AMD technologies and python coding.
 
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+This is the model card of a 🤗 transformers model that has been pushed on the Hub.  
+This model card has been automatically generated.
 
 - **Developed by:** David Silverstein
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
 - **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
+- **Language(s) (NLP):** English, Python
 - **License:** [More Information Needed]
 - **Finetuned from model meta-llama/Meta-Llama-3.1-8B-Instruct**
 
 ### Model Sources [optional]
-
 <!-- Provide the basic links for the model. -->
 
 - **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
 
 ## Uses
-
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-Can be used as a development assistant when using AMD technologies and python in on-premise environments.
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+Can be used as a development assistant when using AMD technologies and python  
+in on-premise environments.
 
 ## Bias, Risks, and Limitations
-
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
 [More Information Needed]
@@ -67,7 +42,8 @@ Can be used as a development assistant when using AMD technologies and python in
 
 <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+Users (both direct and downstream) should be made aware of the risks, biases and  
+limitations of the model. More information needed for further recommendations.
 
 ## How to Get Started with the Model
 
@@ -84,129 +60,32 @@ llm = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat1
 
 ## Training Details
 
-Torchtune was used for full finetuning, for 5 epochs on a single Instinct MI210 GPU. The training set consisted
-of 1658 question/answer pairs in Alpaca format.
+Torchtune was used for full finetuning, for 5 epochs on a single Instinct MI210 GPU.  
+The training set consisted of 1658 question/answer pairs in Alpaca format.
 
 ### Training Data
-
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
 [More Information Needed]
 
 ### Training Procedure
-
 <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
 
 #### Preprocessing [optional]
-
 [More Information Needed]
 
-
 #### 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 -->
 
-#### Speeds, Sizes, Times [optional]
-
-<!-- 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. -->
 
 ### Testing Data, Factors & Metrics
 
 #### Testing Data
-
 <!-- 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. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## 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
 
-This model is a finetuned version of Llama 3.1, which is an auto-regressive language model that uses
-an optimized transformer architecture.
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**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]
+This model is a finetuned version of Llama 3.1, which is an auto-regressive language  
+model that uses an optimized transformer architecture.