Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+- unsloth
+- Agriculture
+- QA
+- LLM
+datasets:
+- KisanVaani/agriculture-qa-english-only
+language:
+- en
+base_model:
+- unsloth/Llama-3.2-3B-Instruct
+new_version: ShuklaShreyansh/Agro-QA
+pipeline_tag: question-answering
+library_name: transformers
+---
+
+
+
+# Model Card for Agro-QA
+
+This model is fine-tuned for agricultural question-answering tasks. It leverages the Llama-3.2-3B-Instruct model to address a variety of topics in agriculture, such as crop selection, pest management, irrigation, and farming best practices.
+
+## Model Details
+
+### Model Description
+
+- **Developed by:** Shukla Shreyansh
+- **Model type:** Question Answering (QA)
+- **Language(s) (NLP):** English
+- **License:** Apache-2.0
+- **Finetuned from model:** [unsloth/Llama-3.2-3B-Instruct](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct)
+
+---
+
+## Uses
+
+### Direct Use
+
+The model is intended for question-answering applications specific to agriculture. It provides insights into farming techniques, crop choices, pest management, and related topics.
+
+### Out-of-Scope Use
+
+The model is not designed for non-agriculture-related questions or tasks requiring specialized domain knowledge outside of agriculture.
+
+---
+
+## Training Details
+
+### Training Data
+
+The model is fine-tuned on the [KisanVaani/agriculture-qa-english-only](https://huggingface.co/datasets/KisanVaani/agriculture-qa-english-only) dataset, a curated collection of questions and answers focused on agricultural topics.
+
+### Training Procedure
+
+- **Training regime:** Mixed precision (FP16)
+- **Batch size:** 2 (per device)
+- **Epochs:** 1
+- **Learning rate:** 2e-4
+- **Optimizer:** AdamW with 8-bit precision
+
+---
+
+## Evaluation
+
+### Testing Data
+
+The model is evaluated on a subset of the training dataset to measure its performance in answering agriculture-related questions.
+
+### Metrics
+
+- **Accuracy:** [More Information Needed]
+- **F1 Score:** [More Information Needed]
+
+---
+
+## How to Get Started with the Model
+
+Use the code below to load and use the model:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load tokenizer
+tokenizer = AutoTokenizer.from_pretrained("ShuklaShreyansh/Agro-QA")
+
+# Load model
+model = AutoModelForCausalLM.from_pretrained("ShuklaShreyansh/Agro-QA").to("cuda")
+
+# Example usage
+messages = [{"role": "user", "content": "What are the best rabi crops to grow?"}]
+inputs = tokenizer.apply_chat_template(messages, tokenize=True, return_tensors="pt").to("cuda")
+output = model.generate(input_ids=inputs['input_ids'], max_new_tokens=128)
+print(tokenizer.decode(output[0]))
+```
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## 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.
+
+## 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]