metadata

datasets:
  - tiiuae/falcon-refinedweb
  - pankajmathur/WizardLM_Orca
language:
  - en
  - de
  - es
  - fr
inference: false

🇰🇷 quantumaikr/falcon-180B-WizardLM_Orca

quantumaikr/falcon-180B-WizardLM_Orca is a 180B parameters causal decoder-only model built by quantumaikr based on Falcon-180B-chat

How to Get Started with the Model

To run inference with the model in full bfloat16 precision you need approximately 8xA100 80GB or equivalent.

from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch

model = "quantumaikr/falcon-180B-WizardLM_Orca"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
    device_map="auto",
)
sequences = pipeline(
   "Girafatron is obsessed with giraffes, the most glorious animal on the face of this Earth. Giraftron believes all other animals are irrelevant when compared to the glorious majesty of the giraffe.\nDaniel: Hello, Girafatron!\nGirafatron:",
    max_length=200,
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id,
)
for seq in sequences:
    print(f"Result: {seq['generated_text']}")

Contact

🇰🇷 www.quantumai.kr

🇰🇷 hi@quantumai.kr [초거대언어모델 기술도입 문의환영]