Update README.md

README.md

@@ -42,7 +42,8 @@ The intended use of BLING models is two-fold:
 1.  Provide a high-quality Instruct models that can run on a laptop for local testing.  We have found it extremely useful when building a
    proof-of-concept, or working with sensitive enterprise data that must be closely guarded, especially in RAG use cases.
 
-2.  Push the state of the art for smaller Instruct-following models in the 1B - 7B range.
+2.  Push the state of the art for smaller Instruct-following models in the 1B - 7B range through improved fine-tuning datasets and targeted "instruction" tasks.
+
 
 ### Direct Use
 
@@ -56,6 +57,8 @@ on a narrower set of Instructions more suitable to a ~1B parameter GPT model.
 BLING is ideal for rapid prototyping, testing, and the ability to perform an end-to-end workflow locally on a laptop without
 having to send sensitive information over an Internet-based API.
 
+The first BLING models have been trained on question-answering, key-value extraction, and basic summarization as the core instruction types.
+
 
 [More Information Needed]
 
@@ -69,7 +72,7 @@ having to send sensitive information over an Internet-based API.
 
 <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-1.  BLING is not designed for 'chat-bot' or 'consumer-oriented' applications.  
+1.  BLING is not designed for 'chat-bot' or 'consumer-oriented' applications. 
 
 2.  BLING is not optimal for most production applications, other than simple and highly specific use cases.
 
@@ -85,68 +88,37 @@ mitigate potential bias and safety.    We would strongly discourage any use of B
 
 [More Information Needed]
 
-### 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.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
+The fastest way to get started with BLING is through direct import in transformers:
 
-[More Information Needed]
-
-## Training Details
+model = AutoModelForCausalLM.from_pretrained("llmware/bling-1b-0.1")
+tokenizer = AutoTokenizer.from_pretrained("llmware/bling-1b-0.1")
 
-### Training Data
+The BLING model was fine-tuned with a simple "<human> and <bot> wrapper", so to get the best results, wrap inference entries as:
 
-<!-- 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. -->
+full_prompt = "<human>: " + my_prompt + "\n" + "<bot>: "
 
-[More Information Needed]
+The BLING model was fine-tuned with closed-context samples, which assume generally that the prompt consists of sub-parts:
 
-### Training Procedure 
+1.  Text Passage Context, and
+2.  Specific question or instruction based on the text passage
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+To get the best results, package "my_prompt" as follows:
 
-#### 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 -->
+my_prompt = {{text_passage}} + "\n" + {{question/instruction}}
 
 
 ## 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 Contact
 
-## Model Card Authors [optional]
+Darren Oberst & llmware team
 
-[More Information Needed]
+Please reach out anytime if you are interested in this research program and would like to participate and work with us!
 
-## Model Card Contact
-
-[More Information Needed]