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--- |
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license: apache-2.0 |
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datasets: |
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- HuggingFaceH4/ultrachat_200k |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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This model is a finetuned version of ```gpt2``` using ```HuggingFaceH4/ultrachat_200k``` |
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## Model description |
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GPT-2 is a transformers model pre-trained on a very large corpus of English data in a self-supervised fashion. This |
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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 |
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of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, |
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it was trained to guess the next word in sentences. |
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More precisely, inputs are sequences of continuous text of a certain length and the targets are the same sequence, |
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shifting one token (word or piece of word) to the right. The model uses a masking mechanism to make sure the |
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predictions for the token `i` only use the inputs from `1` to `i` but not the future tokens. |
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This way, the model learns an inner representation of the English language that can then be used to extract features |
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useful for downstream tasks. The model is best at what it was trained for, however, which is generating texts from a |
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prompt. |
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### To use this model |
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```python |
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>>> from transformers import AutoTokenizer, AutoModelForCausalLM |
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>>> model_name = "Sharathhebbar24/chat_gpt2" |
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>>> model = AutoModelForCausalLM.from_pretrained(model_name) |
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>>> tokenizer = AutoTokenizer.from_pretrained("gpt2") |
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>>> def generate_text(prompt): |
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>>> inputs = tokenizer.encode(prompt, return_tensors='pt') |
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>>> outputs = mod1.generate(inputs, max_length=64, pad_token_id=tokenizer.eos_token_id) |
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>>> generated = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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>>> return generated[:generated.rfind(".")+1] |
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>>> prompt = """ |
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>>> user: what are you? |
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>>> assistant: I am a Chatbot intended to give a python program |
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>>> user: hmm, can you write a python program to print Hii Heloo |
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>>> assistant: Sure Here is a python code.\n print("Hii Heloo") |
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>>> user: Can you write a Linear search program in python |
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>>> """ |
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>>> res = generate_text(prompt) |
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>>> res |
