from transformers import BloomTokenizerFast, BloomForCausalLM

model_name_or_path = "WangZeJun/bloom-820m-chat"

tokenizer = BloomTokenizerFast.from_pretrained(model_name_or_path)
model = BloomForCausalLM.from_pretrained(model_name_or_path).cuda()
model = model.eval()

input_pattern = "{}</s>"
text = "你好"
input_ids = tokenizer(input_pattern.format(text), return_tensors="pt").input_ids
input_ids = input_ids.cuda()

outputs = model.generate(input_ids, do_sample=True, max_new_tokens=1024, top_p=0.85,
    temperature=0.3, repetition_penalty=1.2, eos_token_id=tokenizer.eos_token_id)

input_ids_len = input_ids.size(1)
response_ids = outputs[0][input_ids_len:]
response = tokenizer.decode(response_ids)
print(response)

RichardErkhov/WangZeJun_-_bloom-820m-chat-4bits

Original model description:

license: bigscience-bloom-rail-1.0

RichardErkhov/
WangZeJun_-_bloom-820m-chat-4bits