Downloads · 30 days
295
4% of all-time downloads
RichardErkhov/diabolic6045_-_harry_potter_chatbot-gguf
diabolic6045_-_harry_potter_chatbot-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
295
4% of all-time downloads
All-time downloads
7.7K
Public
Repo size
5 GB
Likes
3
Public
Click a slice to open those files.
.gguf5.8 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
harry_potter_chatbot - GGUF
| Name | Quant method | Size |
|---|---|---|
| harry_potter_chatbot.Q2_K.gguf | Q2_K | 0.17GB |
| harry_potter_chatbot.IQ3_XS.gguf | IQ3_XS | 0.18GB |
| harry_potter_chatbot.IQ3_S.gguf | IQ3_S | 0.19GB |
| harry_potter_chatbot.Q3_K_S.gguf | Q3_K_S | 0.19GB |
| harry_potter_chatbot.IQ3_M.gguf | IQ3_M | 0.2GB |
| harry_potter_chatbot.Q3_K.gguf | Q3_K | 0.21GB |
| harry_potter_chatbot.Q3_K_M.gguf | Q3_K_M | 0.21GB |
| harry_potter_chatbot.Q3_K_L.gguf | Q3_K_L | 0.23GB |
| harry_potter_chatbot.IQ4_XS.gguf | IQ4_XS | 0.22GB |
| harry_potter_chatbot.Q4_0.gguf | Q4_0 | 0.23GB |
| harry_potter_chatbot.IQ4_NL.gguf | IQ4_NL | 0.23GB |
| harry_potter_chatbot.Q4_K_S.gguf | Q4_K_S | 0.23GB |
| harry_potter_chatbot.Q4_K.gguf | Q4_K | 0.25GB |
| harry_potter_chatbot.Q4_K_M.gguf | Q4_K_M | 0.25GB |
| harry_potter_chatbot.Q4_1.gguf | Q4_1 | 0.25GB |
| harry_potter_chatbot.Q5_0.gguf | Q5_0 | 0.27GB |
| harry_potter_chatbot.Q5_K_S.gguf | Q5_K_S | 0.27GB |
| harry_potter_chatbot.Q5_K.gguf | Q5_K | 0.29GB |
| harry_potter_chatbot.Q5_K_M.gguf | Q5_K_M | 0.29GB |
| harry_potter_chatbot.Q5_1.gguf | Q5_1 | 0.29GB |
| harry_potter_chatbot.Q6_K.gguf | Q6_K | 0.32GB |
| harry_potter_chatbot.Q8_0.gguf | Q8_0 | 0.41GB |
Original model description:
This model is a chatbot designed to generate responses in the style of Harry Potter, the protagonist from J.K. Rowling's popular book series and its movie adaptations.
The harry_potter_chatbot is based on the DialoGPT-medium model, a powerful GPT-based architecture designed for generating conversational responses. It has been fine-tuned on a dataset of Harry Potter's dialogues from movie transcripts.
You can use this model to generate responses for a given input text using the following code:
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("diabolic6045/harry_potter_chatbot")
model = AutoModelForCausalLM.from_pretrained("diabolic6045/harry_potter_chatbot")
input_text = "What's your favorite spell?"
input_tokens = tokenizer.encode(input_text, return_tensors='pt')
output_tokens = model.generate(input_tokens, max_length=50, num_return_sequences=1)
output_text = tokenizer.decode(output_tokens[0], skip_special_tokens=True)
print(output_text)
This model is specifically designed to generate responses in the style of Harry Potter and may not provide accurate or coherent answers to general knowledge questions. It may also sometimes generate inappropriate responses. Be cautious while using this model in a public setting or for critical applications.
The model was fine-tuned on a dataset of Harry Potter's dialogues from movie transcripts. The dataset was collected from publicly available movie scripts and includes conversations and quotes from various Harry Potter films.
This model was trained using the Hugging Face Transformers library, and it is based on the DialoGPT-medium model by Microsoft. Special thanks to the Hugging Face team and Microsoft for their contributions to the NLP community.
Feel free to test the model and provide feedback or report any issues. Enjoy chatting with Harry Potter!