Create README.md

README.md

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+---
+license: mit
+datasets:
+- codeparrot/codeparrot-clean
+tags:
+- text-generation
+- code-generation
+- gpt2-large
+widget:
+- text: >-
+    def hello_world():
+  example_title: Code Generation Example 1
+- text: >-
+    
+  example_title: Code Generation Example 2
+pipeline_tag: text-generation
+inference:
+  parameters:
+    max_new_tokens: 30
+    temperature: 0.5
+    num_return_sequences: 1
+    do_sample: true
+---
+
+# Code Generation using GPT2-Large
+This is a GPT2-large model that's further fine-tuned on the Codeparrot clean dataset with a custom metric focused on code generation. <br>
+I've further trained the tokenizer initialized from the GPT2-large on the same dataset to better align the tokenization for generating code.
+
+## Model description
+This Model has the same architecture and Parameters as the GPT2-large model. Please refer to this [link](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf) to know more about the model details.
+
+## Intended Use & Limitations
+This model is intended to generate code for the required function based on a small description of the output required.<br>
+
+**Note:** The model is primarily trained with an objective of code generation.
+
+## Usage
+
+You can use this model directly to get the summaries:
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load Code Generator LLM and tokenizer from checkpoint
+tokenizer = AutoTokenizer.from_pretrained("DeathReaper0965/gpt2_large_code_generator/", )
+model = AutoModelForCausalLM.from_pretrained("DeathReaper0965/gpt2_large_code_generator/")
+
+model = model.to("cuda" if torch.cuda.is_available() else "cpu")
+
+inputs = tokenizer("def hello_world():", return_tensors="pt").to("cuda")
+outputs = model.generate(**inputs,
+                         max_new_tokens= 30,
+                         temperature= 0.5,
+                         num_return_sequences= 1)
+
+print(tokenizer.batch_decode(outputs)[0])
+
+###########OUTPUT###########
+def hello_world():
+    return "Hello World!"
+
+@app.route("/hello_world")
+def hello_world():
+    return "Hello World!"
+```
+
+> Designed and Developed with <span style="color: #e25555;">&hearts;</span> by [Praneet](https://deathreaper0965.github.io/) | [LinkedIn](http://linkedin.com/in/deathreaper0965) | [GitHub](https://github.com/DeathReaper0965/)