README

README.md

@@ -3,196 +3,222 @@ library_name: transformers
 tags: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Model Card for mAInframer-1
 
+Bloob model for auto-complete in the Cobol programming language.
 
 ## Model Details
 
 ### 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.
+mAInframer is a series of models with different parameter counts: 7b, 13b, 34b.
 
-- **Developed by:** [More Information Needed]
-- **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]
+These models are pretrained on code (Codellama base models) and fine-tuned on Cobol code.
 
-### Model Sources [optional]
 
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Developed by: Bloop** 
+- **Finetuned from model: Codellama** 
 
 ## 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. -->
-
-### 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]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[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.
+This model can be used for code completion and fill-in-the middle (Cobol).
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
-
-[More Information Needed]
+Model loading:
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model = AutoModelForCausalLM.from_pretrained("bloopai/mAInframer-7b", device_map="cuda", torch_dtype=torch.bfloat16)
+tokenizer = AutoTokenizer.from_pretrained("codellama/CodeLlama-7b-hf")
+```
+
+### Completion:
+
+```python
+prompt = '''       IDENTIFICATION DIVISION.
+       PROGRAM-ID.  SUM-OF-CUBES.
+       ENVIRONMENT DIVISION.
+       
+       INPUT-OUTPUT SECTION.
+
+       DATA DIVISION.
+       WORKING-STORAGE SECTION.
+       
+       01 STEP         PIC S9(10).
+       01 CUBE         PIC 9(7).
+       01 CUBE-SUM     PIC 9(7) VALUE 0.
+
+       LINKAGE SECTION.
+
+       01 LINKED-ITEMS.
+           05 L-MAX-STEP PIC S9(10).
+           05 RESULT PIC S9(10).
+
+      * 
+      * Given an integer number, return the sum of the of all the integers below it.
+      * 
+      * Example:
+      * 
+      * sum_of_cubes(3) == 1**3 + 2**3 == 9
+      * sum_of_cubes(5) == 100
+      *  
+
+      * Store the result in the RESULT variable and mark the end of your program with END PROGRAM
+'''
+inputs = tokenizer.encode(prompt, return_tensors="pt", add_special_tokens=False).to("cuda")
+outputs = model.generate(inputs, max_new_tokens=250, use_cache=True, do_sample=False, repetition_penalty=1.1)
+print(self.tokenizer.decode(outputs[0]))
+```
+
+Result:
+```cobol
+       IDENTIFICATION DIVISION.
+       PROGRAM-ID.  SUM-OF-CUBES.
+       ENVIRONMENT DIVISION.
+       
+       INPUT-OUTPUT SECTION.
+
+       DATA DIVISION.
+       WORKING-STORAGE SECTION.
+       
+       01 STEP         PIC S9(10).
+       01 CUBE         PIC 9(7).
+       01 CUBE-SUM     PIC 9(7) VALUE 0.
+
+       LINKAGE SECTION.
+
+       01 LINKED-ITEMS.
+           05 L-MAX-STEP PIC S9(10).
+           05 RESULT PIC S9(10).
+
+      * 
+      * Given an integer number, return the sum of the of all the integers below it.
+      * 
+      * Example:
+      * 
+      * sum_of_cubes(3) == 1**3 + 2**3 == 9
+      * sum_of_cubes(5) == 100
+      *  
+
+      * Store the result in the RESULT variable and mark the end of your program with END PROGRAM
+
+       PROCEDURE DIVISION USING LINKED-ITEMS.
+           MOVE L-MAX-STEP TO STEP.
+           PERFORM VARYING STEP FROM 1 BY 1 UNTIL STEP > L-MAX-STEP
+               COMPUTE CUBE = STEP ** 3
+               ADD CUBE TO CUBE-SUM
+           END-PERFORM.
+           DISPLAY CUBE-SUM.
+           MOVE CUBE-SUM TO RESULT.
+           GOBACK.
+           
+       END PROGRAM SUM-OF-CUBES.
+```
+
+### Infilling
+
+Follow the format: `<PRE>prefix<SUF>suffix<MID>`
+
+To complete `PROCEDURE DIVISION` and infill `WORKING STORAGE SECTION.` to solve [CobolEval](https://github.com/BloopAI/COBOLEval) problems:
+
+```python
+prompt = '''<PRE>       IDENTIFICATION DIVISION.
+       PROGRAM-ID.  SUM-OF-CUBES.
+       ENVIRONMENT DIVISION.
+       
+       INPUT-OUTPUT SECTION.
+
+       DATA DIVISION.<SUF>
+
+       LINKAGE SECTION.
+
+       01 LINKED-ITEMS.
+           05 L-MAX-STEP PIC S9(10).
+           05 RESULT PIC S9(10).
+
+      * 
+      * Given an integer number, return the sum of the of all the integers below it.
+      * 
+      * Example:
+      * 
+      * sum_of_cubes(3) == 1**3 + 2**3 == 9
+      * sum_of_cubes(5) == 100
+      *  
+
+      * Store the result in the RESULT variable and mark the end of your program with END PROGRAM'''
+```
+
+Result:
+```cobol
+<PRE>       IDENTIFICATION DIVISION.
+       PROGRAM-ID. MAX-ELEMENT.
+
+       ENVIRONMENT DIVISION.
+       
+       INPUT-OUTPUT SECTION.
+
+       DATA DIVISION.<SUF>
+       LINKAGE SECTION.
+
+       01 LINKED-ITEMS.
+           05 L-L OCCURS 100 TIMES INDEXED BY NI PIC S9(10).
+           05 RESULT PIC S9(10).
+
+      * Return maximum element in the list.
+      * >>> max_element([1, 2, 3])
+      * 3
+      * >>> max_element([5, 3, -5, 2, -3, 3, 9, 0, 123, 1, -10])
+      * 123
+      * 
+
+      * Store the result in the RESULT variable and mark the end of your program with END PROGRAM
+
+       PROCEDURE DIVISION USING LINKED-ITEMS.
+           MOVE ZERO TO WS-MAX-VALUE.
+           PERFORM VARYING NI FROM 1 BY 1 UNTIL NI > 100
+               IF L-L (NI) > WS-MAX-VALUE THEN
+                   MOVE L-L (NI) TO WS-MAX-VALUE
+               END-IF
+           END-PERFORM.
+           DISPLAY 'THE MAXIMUM ELEMENT IS: ' WS-MAX-VALUE.
+           MOVE WS-MAX-VALUE TO RESULT.
+           GOBACK.
+           
+       END PROGRAM MAX-ELEMENT.
+
+<MID>
+       WORKING-STORAGE SECTION.
+       
+       01 WS-MAX-VALUE PIC S9(10) VALUE ZERO.
+
+```
 
 ## Training Details
 
-### 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
+Base model: Codellama
+Finetuning type: LoRA
 
-#### 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. -->
+### Training Data
 
-[More Information Needed]
+Stack-v2(Cobol) + Stack Overflow (Cobol) + Web scraped Cobol + Synthetic Cobol data
 
 #### 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
-
-[More Information Needed]
-
-### 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. -->
+[CobolEval](https://github.com/BloopAI/COBOLEval) is an adaptation of HumanEval where the problems are translated to Cobol.
 
-[More Information Needed]
+| **Model**            | CobolEval (pass@1) | 
+|----------------------|--------------------|
+| **mAInframer-7b**    | 6.16   | 
+| **mAInframer-13b**   | 8.90   |
+| **mAInframer-34b**   | 10.27  |
 
-## More Information [optional]
 
-[More Information Needed]
+## Citation 
 
-## Model Card Authors [optional]
+[Blog post]() 
 
-[More Information Needed]
 
 ## Model Card Contact