Dedicated Endpoints
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Container
Run this model inference with full control and performance in your environment.
Get help setting up a custom Dedicated Endpoints.
Talk with our engineer to get a quote for reserved GPU instances with discounts.
README
License: apache-2.0Model Description
- Task: Text Generation / Question Generation (توليد أسئلة واختبارات)
- Languages Supported: Arabic and English
- Intended Use: Educational applications, teachers' assistance, and automatic quiz generation.
How to use (كيفية الاستخدام برمجياً)
python
from transformers import AutoModelForCausalLM, AutoTokenizerimport torchmodel_id = "oewis16/mistral-exam-generator"tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained(model_id,torch_dtype=torch.float16,device_map="auto")prompt = "اكتب سؤال اختيار من متعدد عن الذكاء الاصطناعي مع الإجابات:"inputs = tokenizer(prompt, return_tensors="pt").to("cuda")outputs = model.generate(**inputs, max_new_tokens=150)print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Model provider
medodeyaa
Model tree
Base
mistralai/Mistral-7B-v0.1
Quantized
this model
Modalities
Input
Text
Output
Text
Pricing
Dedicated Endpoints
View detailsSupported Functionality
Model APIs
Dedicated Endpoints
Container
More information