You can deploy this model and start earning money today!

RichardErkhov/
peaceAsh_-_smolcourse_chapter1-gguf

Name: peaceAsh_-_smolcourse_chapter1-gguf
Availability: InStock

Views

No views yet

Quantization made by Richard Erkhov.

Github

Discord

Request more models

smolcourse_chapter1 - GGUF

Model creator: https://huggingface.co/peaceAsh/
Original model: https://huggingface.co/peaceAsh/smolcourse_chapter1/

Name	Quant method	Size
smolcourse_chapter1.Q2_K.gguf	Q2_K	0.08GB
smolcourse_chapter1.IQ3_XS.gguf	IQ3_XS	0.08GB
smolcourse_chapter1.IQ3_S.gguf	IQ3_S	0.08GB
smolcourse_chapter1.Q3_K_S.gguf	Q3_K_S	0.08GB
smolcourse_chapter1.IQ3_M.gguf	IQ3_M	0.08GB
smolcourse_chapter1.Q3_K.gguf	Q3_K	0.09GB
smolcourse_chapter1.Q3_K_M.gguf	Q3_K_M	0.09GB
smolcourse_chapter1.Q3_K_L.gguf	Q3_K_L	0.09GB
smolcourse_chapter1.IQ4_XS.gguf	IQ4_XS	0.09GB
smolcourse_chapter1.Q4_0.gguf	Q4_0	0.09GB
smolcourse_chapter1.IQ4_NL.gguf	IQ4_NL	0.09GB
smolcourse_chapter1.Q4_K_S.gguf	Q4_K_S	0.1GB
smolcourse_chapter1.Q4_K.gguf	Q4_K	0.1GB
smolcourse_chapter1.Q4_K_M.gguf	Q4_K_M	0.1GB
smolcourse_chapter1.Q4_1.gguf	Q4_1	0.09GB
smolcourse_chapter1.Q5_0.gguf	Q5_0	0.1GB
smolcourse_chapter1.Q5_K_S.gguf	Q5_K_S	0.1GB
smolcourse_chapter1.Q5_K.gguf	Q5_K	0.1GB
smolcourse_chapter1.Q5_K_M.gguf	Q5_K_M	0.1GB
smolcourse_chapter1.Q5_1.gguf	Q5_1	0.1GB
smolcourse_chapter1.Q6_K.gguf	Q6_K	0.13GB
smolcourse_chapter1.Q8_0.gguf	Q8_0	0.13GB

Original model description:

base_model: HuggingFaceTB/SmolLM2-135M library_name: transformers model_name: sft_output tags:

generated_from_trainer
trl
sft licence: license

Model Card for sft_output

This model is a fine-tuned version of HuggingFaceTB/SmolLM2-135M. It has been trained using TRL.

Quick start

python

from transformers import pipeline

question = "Can you write a python function to add 2 numbers?"
generator = pipeline("text-generation", model="peaceAsh/smolcourse_chapter1", 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: 0.12.1
Transformers: 4.46.3
Pytorch: 2.5.1
Datasets: 3.1.0
Tokenizers: 0.20.3

Citations

Cite TRL as:

bibtex

@misc{vonwerra2022trl,
	title        = {{TRL: Transformer Reinforcement Learning}},
	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}

RichardErkhov/peaceAsh_-_smolcourse_chapter1-gguf