| --- |
| license: apache-2.0 |
| datasets: |
| - HuggingFaceH4/ultrachat_200k |
| - mlabonne/CodeLlama-2-20k |
| - Intel/orca_dpo_pairs |
| language: |
| - en |
| pipeline_tag: text-generation |
| tags: |
| - gpt2 |
| - dpo |
| --- |
| |
| This model is a finetuned version of ```Sharathhebbar24/chat_gpt2_dpo``` using ```mlabonne/CodeLlama-2-20k``` |
|
|
| ## Model description |
|
|
| GPT-2 is a transformers model pre-trained on a very large corpus of English data in a self-supervised fashion. This |
| means it was pre-trained on the raw texts only, with no humans labeling them in any way (which is why it can use lots |
| of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, |
| it was trained to guess the next word in sentences. |
|
|
| More precisely, inputs are sequences of continuous text of a certain length and the targets are the same sequence, |
| shifting one token (word or piece of word) to the right. The model uses a masking mechanism to make sure the |
| predictions for the token `i` only use the inputs from `1` to `i` but not the future tokens. |
|
|
| This way, the model learns an inner representation of the English language that can then be used to extract features |
| useful for downstream tasks. The model is best at what it was trained for, however, which is generating texts from a |
| prompt. |
|
|
| ### To use this model |
|
|
| ```python |
| >>> from transformers import AutoTokenizer, AutoModelForCausalLM |
| >>> model_name = "Sharathhebbar24/chat_gpt2" |
| >>> model = AutoModelForCausalLM.from_pretrained(model_name) |
| >>> tokenizer = AutoTokenizer.from_pretrained(model_name) |
| >>> def generate_text(prompt): |
| >>> inputs = tokenizer.encode(prompt, return_tensors='pt') |
| >>> outputs = model.generate(inputs, max_length=64, pad_token_id=tokenizer.eos_token_id) |
| >>> generated = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| >>> return generated[:generated.rfind(".")+1] |
| >>> prompt = """ |
| >>> user: what are you? |
| >>> assistant: I am a Chatbot intended to give a python program |
| >>> user: hmm, can you write a python program to print Hii Heloo |
| >>> assistant: Sure Here is a python code.\n print("Hii Heloo") |
| >>> user: Can you write a Linear search program in python |
| >>> """ |
| >>> res = generate_text(prompt) |
| >>> res |
| ``` |
