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finnstrom3693
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smol-lm-135m-lss-en

Text Generation
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text-generation-inference
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Model Information

This Model is under development there might be chance it repaired in private. in future each version and update dataset experiment will replace in this one repo.

In case there break in model or become overfit visit my stable model on kaggle : https://www.kaggle.com/models/finnstrom/smol-lm-135m-lss-en

There will late change in tested section so model output will be more relevant to stable version.

Model Usage Code 

from transformers import pipeline,set_seed,AutoModelForCausalLM
from IPython.display import display,HTML
import torch

precision = 'half' # @param ["half", "full"]
if precision == "half":
    selected_precision = torch.float16
elif precision == "full":
    selected_precision = torch.float32

model_name = "finnstrom3693/smol-lm-135m-lss-en"
model = AutoModelForCausalLM.from_pretrained(model_name,torch_dtype=selected_precision)

import random

seed = random.randint(1, 100000)
set_seed(seed)

seed = 3693 # @param {type:"integer"}
set_seed(seed)

generator = pipeline('text-generation',
                     model=model_name,
                     torch_dtype=selected_precision,
                     device_map="auto")

input_token_count = len(generator.tokenizer.encode(prompt))

type_output = "greedy"
preds = generator(prompt,
                  max_length=256 + input_token_count,
                  min_length=128 + input_token_count,
                  truncation=True,
                  repetition_penalty=1.2,
                  do_sample=False,
                  early_stopping=False,
                  )

html_code = """
<!DOCTYPE html>
<html>
<head>
</head>
<body>
<p>Model Name: {model_name}</p>
<p>Type Output: {type_output}</p>
<p>Prompt: {prompt}</p>
<p>seed: {seed}</p>
<div style='display: inline-block; border: 2px solid black; padding: 10px; width: 300px; height: 300px; overflow: auto;'>
    <p style='font-family: monospace;'>{pred_0}</p>
</div>
</body>
</html>
""".format(
    model_name=model_name,
    type_output=type_output,
    prompt=prompt,
    seed=seed,
    pred_0=preds[0]['generated_text'].replace('\n', '<br>').replace('\\n', '<br>')
)

# Display the styled output
display(HTML(html_code))

Model Test Comparation

Main objective :
creative writing advantage in emotional,psychologycal,kindness,and Light
Secondary Objective :
LSS as Vanguard test dataset ideology catharsis represed(islamic rukyah and other holy knowledge on emotional intelligence) to fight against regard and social maniac who benefit long term emotional suffering of other.
Main theme and context aim test :
Adaptive Story Generation,Psychologycal and Spiritual,Equality and Right,Oppresive and Tense,Peaceful and Serenity,Environmental

LSS plus theme and context :
Light Romance Story,Heatwarming Story,The Power of Relationship,Kindness and Light
Catharsis represed and LMS(Language of Moon and Soul) supporting theme and context :
Sad Story,Unperfect Hero Story,Family Relationship

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Model size
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FP16
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Inference Examples
Text Generation
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Model tree for finnstrom3693/smol-lm-135m-lss-en

Base model

HuggingFaceTB/SmolLM-135M
Finetuned
this model

Dataset used to train finnstrom3693/smol-lm-135m-lss-en