metadata

license: cc-by-sa-4.0

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License

cc-by-sa-4.0

Model Details

Base Model
maywell/Synatra-10.7B-v0.4

Trained On
A100 80GB * 8

Sionic AI에서 GPU 자원을 지원받아 제작되었습니다.

Instruction format

It follows Alpaca format.

Model Benchmark

TBD

Implementation Code

Since, chat_template already contains insturction format above. You can use the code below.

from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained("maywell/Synatra-kiqu-10.7B-v0.4")
tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-kiqu-10.7B-v0.4")

messages = [
    {"role": "user", "content": "바나나는 원래 하얀색이야?"},
]

encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")

model_inputs = encodeds.to(device)
model.to(device)

generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])