Update README.md

README.md

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 ---
 license: mit
+language:
+- en
+datasets:
+- openbmb/UltraFeedback
+model_creator: OpenBMB
+model_name: UltraCM-13b
+model_type: llama
+base_model: openbmb/UltraCM-13b
+library_name: transformers
+pipeline_tag: text-generation
+inference: false
+tags:
+- dpo
+- rlaif
+- preference
+- ultrafeedback
+quantized_by: alvarobartt
 ---
+
+## Model Card for UltraCM-13b-GGUF
+
+[UltraCM-13B](https://huggingface.co/openbmb/UltraCM-13b) is a fine-tuned LLM for completion-critique in order to evaluate
+LLM outputs on helpfulness, truthfulness, honesty, and to what extent the answer follows the given instructions.
+
+UltraCM-13B is a 13b param LLM that was released by [OpenBMB](https://huggingface.co/openbmb), as part of their paper
+[UltraFeedback: Boosting Language Models with High-quality Feedback](https://arxiv.org/abs/2310.01377).
+
+This model contains the quantized variants using the GGUF format, introduced by the [llama.cpp](https://github.com/ggerganov/llama.cpp) team.
+
+### Model Details
+
+#### Model Description
+
+- **Model type:** Llama
+- **Fine-tuned from model:** [Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf)
+- **Created by**: [Meta AI](https://huggingface.co/meta-llama)
+- **Fine-tuned by:** [OpenBMB](https://huggingface.co/openbmb)
+- **Quantized by:** [alvarobartt](https://huggingface.co/alvarobartt)
+- **Language(s) (NLP):** English
+- **License:** Apache 2.0
+
+### Model Files
+
+| Name | Quant method | Bits | Size | Max RAM required | Use case |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+| [UltraCM-13b.q4_k_s.gguf](https://huggingface.co/alvarobartt/UltraCM-13b-GGUF/blob/main/UltraCM-13b.q4_k_s.gguf) | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
+| [UltraCM-13b.q4_k_m.gguf](https://huggingface.co/alvarobartt/UltraCM-13b.GGUF/blob/main/UltraCM-13b.q4_k_m.gguf) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
+| [UltraCM-13b.q5_k_s.gguf](https://huggingface.co/alvarobartt/UltraCM-13b.GGUF/blob/main/UltraCM-13b.q5_k_s.gguf) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
+| [UltraCM-13b.q5_k_m.gguf](https://huggingface.co/alvarobartt/UltraCM-13b.GGUF/blob/main/UltraCM-13b.q5_k_m.gguf) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
+
+**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
+
+### Uses
+
+#### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Citation
+
+Since this is only a GGUF-quantization of the original weights, please refer and cite the original authors instead.
+
+```bibtex
+@misc{cui2023ultrafeedback,
+      title={UltraFeedback: Boosting Language Models with High-quality Feedback}, 
+      author={Ganqu Cui and Lifan Yuan and Ning Ding and Guanming Yao and Wei Zhu and Yuan Ni and Guotong Xie and Zhiyuan Liu and Maosong Sun},
+      year={2023},
+      eprint={2310.01377},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```