Synatra-Mixtral-8x7B
![Synatra-Mixtral-8x7B](/maywell/Synatra-Mixtral-8x7B/resolve/main/Synatra-Mixtral.png)
Synatra-Mixtral-8x7B is a fine-tuned version of the Mixtral-8x7B-Instruct-v0.1 model using Korean datasets.
This model features overwhelmingly superior comprehension and inference capabilities and is licensed under apache-2.0.
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License
OPEN, Apache-2.0.
Model Details
Base Model
mistralai/Mixtral-8x7B-Instruct-v0.1
Trained On
A100 80GB * 6
Instruction format
It follows Alpaca format.
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{input}
### Response:
{output}
Model Benchmark
TBD
Implementation Code
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained("maywell/Synatra-Mixtral-8x7B")
tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-Mixtral-8x7B")
messages = [
{"role": "user", "content": "μμΈμνμΈμ μλμ±μ΄λ‘ μ λν΄μ μμΈν μ€λͺ
ν΄μ€."},
]
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])
Author's Message
This model's training got sponsered by no one but support from people around Earth.
Contact Me on Discord - is.maywell
Follow me on twitter: https://twitter.com/stablefluffy
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