Aratako/Ministral-3-3B-Instruct-2512-BF16-TextOnly

🤗 Hugging Face 来源apache-2.03.4B 参数6.9 GBsafetensors✓ 3 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo Aratako/Ministral-3-3B-Instruct-2512-BF16-TextOnly ./model-folder
需要做种者 →

Ministral-3-3B-Instruct-2512-TextOnly-BF16

This model is the text-only component extracted from the Vision-Language Model mistralai/Ministral-3-3B-Instruct-2512-BF16.

Usage

You can load this model using AutoModelForCausalLM as shown below:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "Aratako/Ministral-3-3B-Instruct-2512-TextOnly-BF16"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    device_map="cuda",
)

messages = [
    {
        "role": "user",
        "content": "Tell me a joke about computers.",
    },
]

input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")

output = model.generate(
    input_ids, max_new_tokens=512, pad_token_id=tokenizer.eos_token_id
)

decoded_output = tokenizer.decode(
    output[0][len(input_ids[0]) :], skip_special_tokens=True
)
print(decoded_output)

Original Model Information

This is a weight extraction of the original VLM. For detailed benchmarks, licensing details, and architectural information, please refer to the original model card: mistralai/Ministral-3-3B-Instruct-2512-BF16