Model: maywell/Synatra-kiqu-7B Source: Original Platform
license
| license |
|---|
| cc-by-sa-4.0 |
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License
cc-by-sa-4.0
Model Details
Base Model
maywell/Synatra-7B-v0.3-dpo
Trained On
A100 80GB * 8
Sionic AI에서 GPU 자원을 지원받아 제작되었습니다.
Instruction format
It follows ChatML 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-7B")
tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-kiqu-7B")
messages = [
{"role": "user", "content": "사회적 합의는 어떤 맥락에서 사용되는 말이야?"},
]
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])
Description