Llama 3.1 8b Phaedo Ext Xl344
This model is a fine-tuned version of unsloth/Meta-Llama-3.1-8B-Instruct. It has been trained using TRL.
Modellquelle
- Art
- LoRA
- Dateigröße
- 160 MB
- Basismodell
- unsloth/Meta-Llama-3.1-8B-Instruct
- Version
- vadapter_model
- Aktualisiert
- 6. Okt. 2026
- Verleger
- @galavoxx
- Downloads
- 0
- Parameter
- 8B
- Quelle
- Hugging Face
Quellenbeschreibung
Model Card for llama-3.1-8b-phaedo-ext-xl344
This model is a fine-tuned version of unsloth/Meta-Llama-3.1-8B-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="galavoxx/llama-3.1-8b-phaedo-ext-xl344", 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: 1.5.1
- Transformers: 5.10.2
- Pytorch: 2.12.0
- Datasets: 5.0.0
- 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}
}
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 1. Sept.
Modellartefakte
1 Artefakt
Modellartefakte
1 Artefaktadapter_model.safetensors
safetensors · 160 MB · SHA-256 7d8afe4470a1…8639 · Hugging Face
HerunterladenQuellenauszüge
3 Auszüge
Quellenauszüge
3 Auszüge--- base_model: unsloth/Meta-Llama-3.1-8B-Instruct library_name: transformers model_name: llama-3.1-8b-phaedo-ext-xl344 tags: - generated_from_trainer - hf_jobs - sft - trl licence: license --- # Model Card for llama-3.1-8b-phaedo-ext-xl344 This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-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="galavoxx/llama-3.1-8b-phaedo-ext-xl344", 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: 1.5.1 - Transformers: 5.10.2 - Pytorch: 2.12.0 - Datasets: 5.0.0 - 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 galavoxx/llama-3.1-8b-phaedo-ext-xl344
Source context: 0 downloads · 0 likes · Library transformers · Repo galavoxx/llama-3.1-8b-phaedo-ext-xl344
