metadata

license: cc-by-sa-4.0
language:
  - ko
  - en
tags:
  - moe

Synatra-Mixtral-8x7B

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 CC-BY-SA.

License

The "Model" is completely free (ie. base model, derivates, merges/mixes) to use for non-commercial purposes as long as the the included cc-by-sa-4.0 license in any parent repository, and the non-commercial use statute remains, regardless of other models' licences.

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": "아인슈타인의 상대성이론에 대해서 자세히 설명해줘."},
]

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.

Support Me

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