Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) phi3-4x4b-v1 - GGUF - Model creator: https://huggingface.co/Fizzarolli/ - Original model: https://huggingface.co/Fizzarolli/phi3-4x4b-v1/ | Name | Quant method | Size | | ---- | ---- | ---- | | [phi3-4x4b-v1.Q2_K.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q2_K.gguf) | Q2_K | 3.79GB | | [phi3-4x4b-v1.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.IQ3_XS.gguf) | IQ3_XS | 4.23GB | | [phi3-4x4b-v1.IQ3_S.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.IQ3_S.gguf) | IQ3_S | 4.47GB | | [phi3-4x4b-v1.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q3_K_S.gguf) | Q3_K_S | 4.47GB | | [phi3-4x4b-v1.IQ3_M.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.IQ3_M.gguf) | IQ3_M | 4.59GB | | [phi3-4x4b-v1.Q3_K.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q3_K.gguf) | Q3_K | 4.97GB | | [phi3-4x4b-v1.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q3_K_M.gguf) | Q3_K_M | 4.97GB | | [phi3-4x4b-v1.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q3_K_L.gguf) | Q3_K_L | 5.39GB | | [phi3-4x4b-v1.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.IQ4_XS.gguf) | IQ4_XS | 5.56GB | | [phi3-4x4b-v1.Q4_0.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q4_0.gguf) | Q4_0 | 5.83GB | | [phi3-4x4b-v1.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.IQ4_NL.gguf) | IQ4_NL | 5.87GB | | [phi3-4x4b-v1.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q4_K_S.gguf) | Q4_K_S | 5.88GB | | [phi3-4x4b-v1.Q4_K.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q4_K.gguf) | Q4_K | 6.25GB | | [phi3-4x4b-v1.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q4_K_M.gguf) | Q4_K_M | 6.25GB | | [phi3-4x4b-v1.Q4_1.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q4_1.gguf) | Q4_1 | 6.46GB | | [phi3-4x4b-v1.Q5_0.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q5_0.gguf) | Q5_0 | 7.1GB | | [phi3-4x4b-v1.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q5_K_S.gguf) | Q5_K_S | 7.1GB | | [phi3-4x4b-v1.Q5_K.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q5_K.gguf) | Q5_K | 7.32GB | | [phi3-4x4b-v1.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q5_K_M.gguf) | Q5_K_M | 7.32GB | | [phi3-4x4b-v1.Q5_1.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q5_1.gguf) | Q5_1 | 7.74GB | | [phi3-4x4b-v1.Q6_K.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q6_K.gguf) | Q6_K | 8.46GB | | [phi3-4x4b-v1.Q8_0.gguf](https://huggingface.co/RichardErkhov/Fizzarolli_-_phi3-4x4b-v1-gguf/blob/main/phi3-4x4b-v1.Q8_0.gguf) | Q8_0 | 10.96GB | Original model description: --- license: mit tags: - phi3 - nlp - moe datasets: - BEE-spoke-data/gutenberg-en-v1-clean - NeelNanda/pile-10k --- # phi 3 4x4b a continually pretrained phi3-mini sparse moe upcycle ## benchmarks ### ran locally | | Microsoft/phi-3-4k-instruct | Fizzarolli/phi3-4x4b-v1 | | ----------------------- | --------------------------- | ----------------------- | | MMLU acc. (0-shot) | **0.6799** | 0.6781 | | Hellaswag acc. (0-shot) | **0.6053** | 0.5962 | | ARC-E acc. (0-shot) | 0.8325 | **0.8367** | | ARC-C acc. (0-shot) | 0.5546 | **0.5606** | honestly i was expecting it to do worse :p, but those are all within a margin of error! so it didn't *lose* any performance, at least ### open llm leaderboard todo! ## support me on ko-fi! [~~please i need money to stay alive and keep making models~~](https://ko-fi.com/fizzai) ## notes *not trained on instruct data.* it's pretty likely that it won't be much different from phi 3 if you use it like that, if not worse due to any forgetting of instruct formats during the continued training. ## future experiments - the datasets for this were literally chosen on a whim. perhaps experiment with a further filtered [HuggingFaceFW/fineweb-edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu)? - actually freeze the gate layers next time (see [Chen et. al, 2023](https://arxiv.org/abs/2303.01610)), oops - MOAR TRAINING, this only went up to ~0.2 of an epoch because i ran out of dolar