01

01-ai/Yi-1.5-9B-Chat

text-generationtransformersapache-2.08.8B params · updated Jun 2024

Usage

usage.pytemplate from repo id
from osai import AutoModelForCausalLM, AutoTokenizer

repo = "01-ai/Yi-1.5-9B-Chat"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, dtype="bfloat16", device_map="auto",
)

msgs = [{"role": "user", "content": "Explain speculative decoding."}]
ids = tok.apply_chat_template(msgs, return_tensors="pt").to(model.device)
print(tok.decode(model.generate(ids, max_new_tokens=256)[0]))

Hardware

Computed from 8.83B parameters × bytes per parameter, plus 20% for activations and KV cache. Not measured.

PrecisionWeightsEstimated VRAMFits on
bf1616.4 GB20 GBL4 24 GB
int88.2 GB9.9 GBCPU or T4 16 GB
nf44.1 GB4.9 GBCPU or T4 16 GB