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README.md

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 ---
-license: mit
+library_name: transformers
+tags: []
 ---
 
-This model is a part of two model series, AryaBhatta-1 and AryaBhatta-2 and is finetuned from HuggingFaceH4/zephyr-7b-gemma-v0.1 or Google/gemma and is finetuned on 9 Indian languages (Hindi, Tamil, Punjabi, Bengali, Gujarati, Oriya, Telugu, Kannada, Malayalam) plus English.
-To improve the resoning and maths skills, we first SFT tune the gemma on Microsoft's Orca datasets.
+# Model Card for Model ID
 
-There are two models. One finetuned on Google's Gemma and one fine-tuned on Zephyr's Gemma base. Repo for other one (Zephyr one): GenVRadmin/AryaBhatta-GemmaOrca-2-Merged
+<!-- Provide a quick summary of what the model is/does. -->
 
-We utilize Orca maths Hindi dataset: GenVRadmin/Aryabhatta-Orca-Maths-Hindi \
-And original Orca maths dataset: microsoft/orca-math-word-problems-200k 
 
-This pushes the MATHS score from 24.3 in Gemma-7B to 25.5 in Zephyr-Gemma and 31.6 in GemmaOrca.
 
-The model is then finetuned on GenVR's Samvaad datasets (GenVRadmin/Samvaad-Indic-Positive and GenVRadmin/Samvaad-Tamil-Mixtral and a subset of GenVRadmin/Samvaad-Mixed-Language-3).
+## Model Details
 
-This is then finetuned on various open sourced datasets like:
+### Model Description
 
-Telugu-LLM-Labs/yahma_alpaca_cleaned_telugu_filtered_and_romanized \
-Telugu-LLM-Labs/teknium_GPTeacher_general_instruct_telugu_filtered_and_romanized \
-abhinand/tamil-alpaca \
-Tensoic/airoboros-3.2_kn \
-Tensoic/gpt-teacher_kn \
-Tensoic/Alpaca-Gujarati \
-HydraIndicLM/bengali_alpaca_dolly_67k \
-Open-Orca/OpenOrca \
-pankajmathur/alpaca_orca \
-OdiaGenAI/Odia_Alpaca_instructions_52k \
-OdiaGenAI/gpt-teacher-roleplay-odia-3k \
-GenVRadmin/Samvaad-Punjabi-Mini \
-pankajmathur/WizardLM_Orca 
+<!-- Provide a longer summary of what this model is. -->
 
-The model achieves following scores on benchmarks:
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-Model	                 AGIEval	GPT4All	TruthfulQA	BigBench	Average ⬇️ \
-AryaBhatta-GemmaOrca      35.9       72.26   53.85       40.35       50.59 \
-zephyr-7b-beta	          37.52	     71.77	 55.26	     39.77	     51.08 \
-zephyr-7b-gemma-v0.1	  34.22	     66.37	 52.19	     37.10	     47.47 \
-mlabonne/Gemmalpaca-7B	  21.6	     40.87	 44.85	     30.49	     34.45 \
-google/gemma-7b-it	      21.33	     40.84	 41.70	     30.25	     33.53 
+- **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]
 
+### Model Sources [optional]
 
+<!-- Provide the basic links for the model. -->
 
-How to use:-
-```
-from peft import AutoPeftModelForCausalLM
-from transformers import AutoTokenizer
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-model = AutoPeftModelForCausalLM.from_pretrained(
-    "GenVRadmin/AryaBhatta-GemmaOrca",
-    load_in_4bit = False,
-    token = hf_token
-)
-tokenizer = AutoTokenizer.from_pretrained("GenVRadmin/AryaBhatta-GemmaOrca")
+## Uses
 
-input_prompt = """
-### Instruction:
-{}
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-### Input:
-{}
+### Direct Use
 
-### Response:
-{}"""
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-input_text = input_prompt.format(
-        "Answer this question about India.", # instruction
-        "Who is the Prime Minister of India", # input
-        "", # output - leave this blank for generation!
-    )
+[More Information Needed]
 
-inputs = tokenizer([input_text], return_tensors = "pt").to("cuda")
+### Downstream Use [optional]
 
-outputs = model.generate(**inputs, max_new_tokens = 300, use_cache = True)
-response = tokenizer.batch_decode(outputs)[0]
-```
+<!-- 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.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## 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
+
+#### 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. -->
+
+[More Information Needed]
+
+#### 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. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]

adapter_model.safetensors

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