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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+openai-gsm8k_meta-llama-Llama-3.2-1B - GGUF
+- Model creator: https://huggingface.co/YWZBrandon/
+- Original model: https://huggingface.co/YWZBrandon/openai-gsm8k_meta-llama-Llama-3.2-1B/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q2_K.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q2_K.gguf) | Q2_K | 0.54GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.IQ3_XS.gguf) | IQ3_XS | 0.58GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.IQ3_S.gguf) | IQ3_S | 0.6GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K_S.gguf) | Q3_K_S | 0.6GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.IQ3_M.gguf) | IQ3_M | 0.61GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K.gguf) | Q3_K | 0.64GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K_M.gguf) | Q3_K_M | 0.64GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q3_K_L.gguf) | Q3_K_L | 0.68GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.IQ4_XS.gguf) | IQ4_XS | 0.7GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_0.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_0.gguf) | Q4_0 | 0.72GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.IQ4_NL.gguf) | IQ4_NL | 0.72GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_K_S.gguf) | Q4_K_S | 0.72GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_K.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_K.gguf) | Q4_K | 0.75GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_K_M.gguf) | Q4_K_M | 0.75GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_1.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q4_1.gguf) | Q4_1 | 0.77GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_0.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_0.gguf) | Q5_0 | 0.83GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_K_S.gguf) | Q5_K_S | 0.83GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_K.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_K.gguf) | Q5_K | 0.85GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_K_M.gguf) | Q5_K_M | 0.85GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_1.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q5_1.gguf) | Q5_1 | 0.89GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q6_K.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q6_K.gguf) | Q6_K | 0.95GB |
+| [openai-gsm8k_meta-llama-Llama-3.2-1B.Q8_0.gguf](https://huggingface.co/RichardErkhov/YWZBrandon_-_openai-gsm8k_meta-llama-Llama-3.2-1B-gguf/blob/main/openai-gsm8k_meta-llama-Llama-3.2-1B.Q8_0.gguf) | Q8_0 | 1.23GB |
+
+
+
+
+Original model description:
+---
+base_model: meta-llama/Llama-3.2-1B
+datasets: openai/gsm8k
+library_name: transformers
+model_name: openai-gsm8k_meta-llama-Llama-3.2-1B
+tags:
+- generated_from_trainer
+- trl
+- sft
+licence: license
+---
+
+# Model Card for openai-gsm8k_meta-llama-Llama-3.2-1B
+
+This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on the [openai/gsm8k](https://huggingface.co/datasets/openai/gsm8k) dataset.
+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="YWZBrandon/openai-gsm8k_meta-llama-Llama-3.2-1B", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yuweiz/ActionEditV1/runs/fz4agnju)
+
+This model was trained with SFT.
+
+### Framework versions
+
+- TRL: 0.12.2
+- 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}}
+}
+```
+