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Kafka Topic Extractor Llama3B Retrained Advanced

Model Card for kafka-topic-extractor-llama3B-retrained-advanced

KindOtherBase modelmeta-llama/Llama-3.2-3B-InstructPublisher@JhanavikSBgrade

Model source

Kind
Other
File size
17.5 MB
Base model
meta-llama/Llama-3.2-3B-Instruct
Updated
Oct 17, 2026
Publisher
@JhanavikS
Tasks
Text generation
Source
Hugging Face

Source description

Model Card for kafka-topic-extractor-llama3B-retrained-advanced

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct. It has been trained using TRL.

Quick start

from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="JhanavikS/kafka-topic-extractor-llama3B-retrained-advanced", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

This model was trained with SFT.

Framework versions

  • TRL: 1.0.0
  • Transformers: 5.0.0
  • Pytorch: 2.10.0+cu128
  • Datasets: 4.8.4
  • Tokenizers: 0.22.2

Citations

Cite TRL as:

@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
license = {Apache-2.0},
url = {https://github.com/huggingface/trl},
year = {2020}
}

Sources

1 source

Model artifacts

1 artifact

adapter_model.safetensors

safetensors · 17.5 MB · SHA-256 d6d5aabfce5f…103d · Hugging Face

Source excerpts

3 excerpts

--- base_model: meta-llama/Llama-3.2-3B-Instruct library_name: transformers model_name: kafka-topic-extractor-llama3B-retrained-advanced tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for kafka-topic-extractor-llama3B-retrained-advanced This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="JhanavikS/kafka-topic-extractor-llama3B-retrained-advanced", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure This model was trained with SFT. ### Framework versions - TRL: 1.0.0 - Transformers: 5.0.0 - Pytorch: 2.10.0+cu128 - Datasets: 4.8.4 - Tokenizers: 0.22.2 ## Citations Cite TRL as: ```bibtex @software{vonwerra2020trl, title = {{TRL: Transformers Reinforcement Learning}}, author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin}, license = {Apache-2.0}, url = {https://github.com/huggingface/trl}, year = {2020} } ```

Source context: 0 downloads · 0 likes · Library transformers · Repo JhanavikS/kafka-topic-extractor-llama3B-retrained-advanced

Source context: 0 downloads · 0 likes · Library transformers · Repo JhanavikS/kafka-topic-extractor-llama3B-retrained-advanced