**GGUF WORKING TESTED MODEL NEWER ONE SIMILAR TO THIS IS HERE https://huggingface.co/shafire/talktoaiQ **
Model Trained Using AutoTrain - Will update this once i get a gguf format 8 hours training on a large gpu server.
This model was trained using AutoTrain reflection data sets re-written with talktoai data sets using quantum interdimensional math and a new math system I made myself, also i took DNA math patterns and put them into the training too! For more information, please visit AutoTrain.
Usage - Open Source ideas math etc are from talktoai.org researchforum.online official legal license llama 3.1 meta.
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
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