QuantumLM
Model Description
QuantumLM
is a Llama2 70B model finetuned on an guanaco, guanaco-unchained Dataset
Usage
Start chatting with QuantumLM-70B-hf
using the following code snippet:
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained("quantumaikr/QuantumLM-70B-hf")
model = AutoModelForCausalLM.from_pretrained("quantumaikr/QuantumLM-70B-hf", torch_dtype=torch.bfloat16, device_map="auto")
system_prompt = "### System:\nYou are QuantumLM, an AI that follows instructions extremely well. Help as much as you can. Remember, be safe, and don't do anything illegal.\n\n"
message = "Write me a poem please"
prompt = f"{system_prompt}### User: {message}\n\n### Assistant:\n"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
output = model.generate(**inputs, do_sample=True, top_p=0.95, top_k=0, max_new_tokens=256)
print(tokenizer.decode(output[0], skip_special_tokens=True))
QuantumLM should be used with this prompt format:
### System:
This is a system prompt, please behave and help the user.
### User:
Your prompt here
### Assistant
The output of QuantumLM
Use and Limitations
Intended Use
These models are intended for research only, in adherence with the CC BY-NC-4.0 license.
Limitations and bias
Although the aforementioned dataset helps to steer the base language models into "safer" distributions of text, not all biases and toxicity can be mitigated through fine-tuning. We ask that users be mindful of such potential issues that can arise in generated responses. Do not treat model outputs as substitutes for human judgment or as sources of truth. Please use it responsibly.
Contact us : hi@quantumai.kr
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