Update README.md

README.md

@@ -1,13 +1,15 @@
 ---
 library_name: transformers
-tags: []
+language:
+- en
+pipeline_tag: text-generation
 ---
 
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-
+Model finetuned specifically for expertise on AMD technologies and python coding.
 
 ## Model Details
 
@@ -17,13 +19,13 @@ tags: []
 
 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:** [More Information Needed]
+- **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]
 - **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Finetuned from model meta-llama/Meta-Llama-3.1-8B-Instruct**
 
 ### Model Sources [optional]
 
@@ -69,12 +71,22 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
+Use the code below to get started with the model. 
+
+import torch  
+from transformers import AutoTokenizer, AutoModelForCausalLM  
+
+model_name = 'davidsi/Llama3_1-8B-Instruct-AMD-python'  
+tokenizer = AutoTokenizer.from_pretrained(model_name)  
+llm = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16)
 
 [More Information Needed]
 
 ## 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.
+
 ### 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. -->
@@ -154,7 +166,8 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ### Model Architecture and Objective
 
-[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.
 
 ### Compute Infrastructure