how to use this shit :
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
repo_id = "iko-01/iko_im3"
# ุจุฏู REPO_BASE ุจุงููู ุฏุฑูุจุช ุนููู ุฃูู ู
ุฑุฉ (ู
ุซูุงู gpt2 ุฃู iko-01/iko-v5e-1)
base_repo = "iko-01/iko-v5e-1"
tokenizer = AutoTokenizer.from_pretrained(base_repo)
model = AutoModelForCausalLM.from_pretrained(repo_id)
model.to("cpu")
def ask_model(question, max_new_tokens=1000):
prompt = f"### User:\n{question.strip()}\n\n### Assistant:\n"
inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True, max_length=1024)
with torch.no_grad():
gen = model.generate(
inputs.input_ids,
attention_mask=inputs.attention_mask,
max_new_tokens=max_new_tokens,
do_sample=True,
top_p=0.95,
temperature=0.9,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id,
)
out = tokenizer.decode(gen[0], skip_special_tokens=True)
if "### Assistant:" in out:
return out.split("### Assistant:")[-1].strip()
return out
print(ask_model("what is API"))
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