π°π· quantumaikr/falcon-180B-chat-instruct
quantumaikr/falcon-180B-chat-instruct 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-chat-instruct"
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']}")
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