Create README.md

README.md

@@ -0,0 +1,62 @@
+* * *
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+## Model Card for AnkiGPT-small
+
+# Model Card for AnkiGPT-small
+
+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
+
+- **Developed by:** [anktechsol.com](www.anktechsol.com)
+- **Shared by:** [More Information Needed - anktechsol]
+- **Model type:** Causal Language Model
+- **Language(s) (NLP):** English, potentially aspects of Indian languages/Hinglish due to fine-tuning data.
+- **License:** (Specify the license of the fine-tuned model, often inherited from the base model or dataset. DialoGPT uses MIT license, check the dataset license.)
+- **Finetuned from model [optional]:** `microsoft/DialoGPT-small`
+
+### Model Sources [optional]
+
+- **Repository:** `https://huggingface.co/anktechsol/ankiGPT-small` (This will be the link after pushing to the hub)
+
+## Uses
+
+### Direct Use
+
+This model can be used for text generation, particularly in conversational or narrative contexts, with a potential bias towards topics and linguistic styles present in the fine-tuning dataset (Indian conversational data).
+
+### Downstream Use
+
+This model could potentially be used as a base for further fine-tuning on more specific Indian language tasks or domains.
+
+### Out-of-Scope Use
+
+This model is not suitable for generating factual information, performing critical tasks requiring high accuracy, or deployment in sensitive applications without extensive further evaluation and mitigation of potential biases.
+
+## Bias, Risks, and Limitations
+
+Based on initial testing, the model may exhibit repetitive text generation, especially for longer sequences. The model's knowledge and linguistic style are heavily influenced by the fine-tuning dataset, which may not cover all aspects of Indian languages or culture comprehensively. Biases present in the training data may be reflected in the model's output.
+
+### Recommendations
+
+Users should be aware of the model's limitations in generating coherent long text and potential biases. It is recommended to experiment with different generation parameters (`max_length`, `no_repeat_ngram_size`, sampling strategies) to improve output quality. For any critical applications, thorough testing and human review of generated content are essential.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model using the `transformers` library.
+
+  from transformers import pipeline
+  
+  # Replace "anktechsol/ankiGPT-small" with your actual model ID on the Hugging Face Hub
+  generator = pipeline("text-generation", model="anktechsol/ankiGPT-small")
+  
+  # A detailed prompt related to India
+  prompt = "Write a short story about a day in the life of a student in a bustling Indian city, describing their commute, interactions at school, and a cultural event they attend in the evening. Keep it in hinglish"
+  
+  # Generate text with a reasonable max_length to allow for a detailed story
+  generated_text = generator(prompt, max_length=300, num_return_sequences=1)
+  
+  print(generated_text[0]['generated_text'])