Create README.md

README.md

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+---
+datasets:
+- roneneldan/TinyStories
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+We tried to use the huggingface transformers library to recreate the TinyStories models on Consumer GPU. Output model has 9 million parameters. 
+Tweaked code of springtangent (https://github.com/springtangent/tinystoriestrainer/blob/main/tinystories_train.py)
+Code credit - springtangent
+
+------ EXAMPLE USAGE ---
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("segestic/Tinystories-0.1-9m")
+
+model = AutoModelForCausalLM.from_pretrained("segestic/Tinystories-0.1-9m")
+
+prompt = "Once upon a time there was"
+
+input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+# Generate completion
+output = model.generate(input_ids, max_length = 1000, num_beams=1)
+
+# Decode the completion
+output_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Print the generated text
+print(output_text)