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README.md

@@ -7,6 +7,23 @@ model_type: BERT-Base-Uncased
 model_summary: This model Compares the similarity of two text objects.
 shared_by: Matt Stammers
 finetuned_from: Glue
+repo: https://huggingface.co/MattStammers/test-trainer?text=I+like+you.+I+love+you
+paper: nil
+demo: false
+direct_use: Test it out here
+downstream_use: This is a standalone app
+out_of_scope_use: The model will not work with any very complex sentences or to compare
+  more than 3 statements
+bias_risks_limitations: Biases inherent in Glue also apply here
+bias_recommendations: Do not be surprised if unusual results are obtained
+get_started_code: "``` python \n    # Use a pipeline as a high-level helper\n    \
+  \    from transformers import pipeline\n\n        pipe = pipeline(\"text-classification\"\
+  , model=\"MattStammers/test-trainer\")\n    # Load model directly\n        from\
+  \ transformers import AutoTokenizer, AutoModelForSequenceClassification\n\n    \
+  \    tokenizer = AutoTokenizer.from_pretrained(\"MattStammers/test-trainer\")\n\
+  \        model = AutoModelForSequenceClassification.from_pretrained(\"MattStammers/test-trainer\"\
+  )\n                        "
+training_data: 'see Glue dataset: https://huggingface.co/datasets/glue'
 model-index:
 - name: test_trainer
   results:
@@ -47,8 +64,8 @@ This model Compares the similarity of two text objects.
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
+- **Repository:** https://huggingface.co/MattStammers/test-trainer?text=I+like+you.+I+love+you
+- **Paper [optional]:** nil
 - **Demo [optional]:** [More Information Needed]
 
 ## Uses
@@ -59,37 +76,47 @@ This model Compares the similarity of two text objects.
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-[More Information Needed]
+Test it out here
 
 ### 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]
+This is a standalone app
 
 ### Out-of-Scope Use
 
 <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-[More Information Needed]
+The model will not work with any very complex sentences or to compare more than 3 statements
 
 ## Bias, Risks, and Limitations
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+Biases inherent in Glue also apply here
 
 ### Recommendations
 
 <!-- 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.
+Do not be surprised if unusual results are obtained
 
 ## How to Get Started with the Model
 
 Use the code below to get started with the model.
 
-[More Information Needed]
+``` python 
+    # Use a pipeline as a high-level helper
+        from transformers import pipeline
+
+        pipe = pipeline("text-classification", model="MattStammers/test-trainer")
+    # Load model directly
+        from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+        tokenizer = AutoTokenizer.from_pretrained("MattStammers/test-trainer")
+        model = AutoModelForSequenceClassification.from_pretrained("MattStammers/test-trainer")
+                        
 
 ## Training Details
 
@@ -97,7 +124,7 @@ Use the code below to get started with the model.
 
 <!-- This should link to a Data 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]
+see Glue dataset: https://huggingface.co/datasets/glue
 
 ### Training Procedure