Update README.md

README.md

@@ -13,15 +13,15 @@ tags:
 
 A model fined tuned for sanctions and AML related OFAC FAQ questions with the Swiss AI
 Apertus 8B Instruct model which was then used as teacher and distilled to TinyLlama 1.1B. The model is 6-7 X smaller than the original. Quantization to INT8 should allow even low-memory CPU inference
-deployments if model latency is not a primary concern. FEFT LoRA adapter are included for use with base model.
+deployments if model latency is not a primary concern. PEFT LoRA adapter are included for use with base model.
 
 
 ## Model Details
 
 ### Model Description
 
-The model includes INT8 quantized weights for CPU inference and LoRA adopters for GPU inference with
-amatching base.
+The model includes INT8 quantized weights for CPU inference and a LoRA adapter for GPU inference with
+a matching base.
 
 
 - **Developed by:** Soteria Initiative
@@ -37,12 +37,12 @@ amatching base.
 <!-- Provide the basic links for the model. -->
 
 - **Repository:** https://huggingface.co/SoteriaInitiative/Apertus-8B-Instruct-OFAC-FAQ
-- **Demo:** https://huggingface.co/SoteriaInitiative/Apertus-8B-Instruct-OFAC-FAQnotebook.ipynb
+- **Demo:** _WIP_
 
 ## Uses
 
 Use for chat or assistant applications where compliance or financial crime analysis need to 
-Get answers regarding FATF or OFAC FAQ matters.
+get answers regarding FATF or OFAC FAQ matters.
 
 ### Direct Use
 
@@ -57,7 +57,7 @@ This model is not intended for production deployment.
 ## Bias, Risks, and Limitations
 
 The model is fine tuned for FATF and OFAC FAQ matters and hence should be restricted to such 
-Use cases where this is of a concern.
+use cases where this is of a concern.
 
 
 ### Recommendations
@@ -130,13 +130,9 @@ The following sources where used for fine tuning:
 ### Training Procedure
 
 Supervised fine tuning has been applied to the Apertus 8B Instruct model with a training dataset
-Containing of FAQ question/answer pairs as well as FATF titles and recommendation pairs.
+of FAQ question/answer pairs as well as FATF titles and recommendation pairs.
 
 
-#### 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 -->
-
 
 ## Evaluation