base_model: stabilityai/stablelm-2-zephyr-1_6b
datasets:
- HuggingFaceH4/ultrachat_200k
- allenai/ultrafeedback_binarized_cleaned
- meta-math/MetaMathQA
- WizardLM/WizardLM_evol_instruct_V2_196k
- openchat/openchat_sharegpt4_dataset
- LDJnr/Capybara
- Intel/orca_dpo_pairs
- hkust-nlp/deita-10k-v0
license: other
license_link: https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b/blob/main/LICENSE
language:
- en
model_creator: stabilityai
model_name: stablelm-2-zephyr-1_6b
model_type: stablelm_epoch
inference: false
tags:
- causal-lm
- stablelm_epoch
pipeline_tag: text-generation
prompt_template: |
<|system|>
{{system_message}}<|endoftext|>
<|user|>
{{prompt}}<|endoftext|>
<|assistant|>
quantized_by: brittlewis12
StableLM-2-Zephyr-1.6B GGUF
Original model: StableLM 2 Zephyr 1.6B Model creator: Stability AI
This repo contains GGUF format model files for Stability AI’s StableLM 2 Zephyr 1.6B.
Stable LM 2 Zephyr 1.6B is a 1.6 billion parameter instruction tuned language model inspired by HugginFaceH4's Zephyr 7B training pipeline. The model is trained on a mix of publicly available datasets and synthetic datasets, utilizing Direct Preference Optimization (DPO).
What is GGUF?
GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Converted using an proposed version of llama.cpp (PR #5052)
Prompt template: Zephyr
<|system|>
{{system_message}}<|endoftext|>
<|user|>
{{prompt}}<|endoftext|>
<|assistant|>
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Original Model Evaluations:
Model | Size | MT-Bench |
---|---|---|
Mistral-7B-Instruct-v0.2 | 7B | 7.61 |
Llama2-Chat | 70B | 6.86 |
stablelm-zephyr-3b | 3B | 6.64 |
MPT-30B-Chat | 30B | 6.39 |
stablelm-2-zephyr-1.6b | 1.6B | 5.42 |
Falcon-40B-Instruct | 40B | 5.17 |
Qwen-1.8B-Chat | 1.8B | 4.95 |
dolphin-2.6-phi-2 | 2.7B | 4.93 |
phi-2 | 2.7B | 4.29 |
TinyLlama-1.1B-Chat-v1.0 | 1.1B | 3.46 |
OpenLLM Leaderboard
Model | Size | Average | ARC Challenge (acc_norm) | HellaSwag (acc_norm) | MMLU (acc_norm) | TruthfulQA (mc2) | Winogrande (acc) | Gsm8k (acc) |
---|---|---|---|---|---|---|---|---|
microsoft/phi-2 | 2.7B | 61.32% | 61.09% | 75.11% | 58.11% | 44.47% | 74.35% | 54.81% |
stabilityai/stablelm-2-zephyr-1_6b | 1.6B | 49.89% | 43.69% | 69.34% | 41.85% | 45.21% | 64.09% | 35.18% |
microsoft/phi-1_5 | 1.3B | 47.69% | 52.90% | 63.79% | 43.89% | 40.89% | 72.22% | 12.43% |
stabilityai/stablelm-2-1_6b | 1.6B | 45.54% | 43.43% | 70.49% | 38.93% | 36.65% | 65.90% | 17.82% |
mosaicml/mpt-7b | 7B | 44.28% | 47.70% | 77.57% | 30.80% | 33.40% | 72.14% | 4.02% |
KnutJaegersberg/Qwen-1_8B-Llamaified* | 1.8B | 44.75% | 37.71% | 58.87% | 46.37% | 39.41% | 61.72% | 24.41% |
openlm-research/open_llama_3b_v2 | 3B | 40.28% | 40.27% | 71.60% | 27.12% | 34.78% | 67.01% | 0.91% |
iiuae/falcon-rw-1b | 1B | 37.07% | 35.07% | 63.56% | 25.28% | 35.96% | 62.04% | 0.53% |
TinyLlama/TinyLlama-1.1B-3T | 1.1B | 36.40% | 33.79% | 60.31% | 26.04% | 37.32% | 59.51% | 1.44% |