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LLama3-8B-Instruct for Japanese

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "hoang1123/llama3-8b-instruct-ja"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

messages = [
    {"role": "system", "content": "あなたは誠実で優秀な日本人アシスタントです。"},
    {"role": "user", "content": "Python で一連の数値の平均を計算する関数を作成します。"},
]

input_ids = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    return_tensors="pt"
).to(model.device)

terminators = [
    tokenizer.eos_token_id,
    tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

outputs = model.generate(
    input_ids,
    max_new_tokens=1024,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))

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Safetensors

Model size

8B params

Tensor type

F32