How to Use

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "DeepMount00/Lexora-Lite-3B"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

prompt = [{'role': 'user', 'content': """Marco ha comprato 5 scatole di cioccolatini. Ogni scatola contiene 12 cioccolatini. Ha deciso di dare 3 cioccolatini a ciascuno dei suoi 7 amici. Quanti cioccolatini gli rimarranno dopo averli distribuiti ai suoi amici?"""}]
inputs = tokenizer.apply_chat_template(
    prompt,
    add_generation_prompt=True,
    return_tensors='pt'
)
tokens = model.generate(
    inputs.to(model.device),
    max_new_tokens=1024,
    temperature=0.001,
    do_sample=True
)

print(tokenizer.decode(tokens[0], skip_special_tokens=False))
Downloads last month
9,533
Safetensors
Model size
3.09B params
Tensor type
BF16
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for DeepMount00/Lexora-Lite-3B

Quantizations
3 models

Datasets used to train DeepMount00/Lexora-Lite-3B