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Yes I usually run Unsloth models, however you are linking to the big model now (355B-A32B), which I can't run on my consumer hardware. The flash model in this
by dajonker 9mo ago
Yes I usually run Unsloth models, however you are linking to the big model now (355B-A32B), which I can't run on my consumer hardware.
The flash model in this thread is more than 10x smaller (30B).
- latchkey 9mo agoThere are a bunch of 4bit quants in the GGUF link and the 0xSero has some smaller stuff too. Might still be too big and you'll need to ungpu poor yourself.
- disiplus 9mo agoyeah there is no way to run 4.7 on a 32g vram this flash is something that im also waiting to try later tonight
- omneity 9mo agoWhy not? Run it with vLLM latest and enable 4bit quantization with bnb, and it will quantize the original safetensors on the fly and fit your vram.
- disiplus 9mo agobecause how huge glm 4.7 is https://huggingface.co/zai-org/GLM-4.7 https://huggingface.co/zai-org/GLM-4.7
- omneity 9mo agoExcept this is GLM 4.7 Flash which has 32B total params, 3B active. It should fit with a decent context window of 40k or so in 20GB of ram at 4b weights quantization and you can save even more by quantizing the activations and KV cache to 8bit.
- disiplus 9mo agoyes, but the parrent link was to the big glm 4.7 that had a bunch of ggufs, the new one at the point of posting did not, nor does it now. im waiting for unsloth guys for the 4.7 flash
- a_e_k 9mo agoWhen the Unsloth quant of the flash model does appear, it should show up as unsloth/... on this page: https://huggingface.co/models?other=base_model:quantized:zai-org/GLM-4.7-Flash https://huggingface.co/models?other=base_model:quantized:zai... Probably as: https://huggingface.co/unsloth/GLM-4.7-Flash-GGUF https://huggingface.co/unsloth/GLM-4.7-Flash-GGUF
- homarp 9mo agoit'a a new architecture. Not yet implemented in llama.cpp issue to follow: https://github.com/ggml-org/llama.cpp/issues/18931 https://github.com/ggml-org/llama.cpp/issues/18931
- dumbmrblah 9mo agoOne thing to consider is that this version is a new architecture, so it’ll take time for Llama CPP to get updated. Similar to how it was with Qwen Next.
- cristoperb 9mo agoApparently it is the same as the DeepseekV3 architecture and already supported by llama.cpp once the new name is added. Here's the PR: https://github.com/ggml-org/llama.cpp/pull/18936 https://github.com/ggml-org/llama.cpp/pull/18936
- khimaros 9mo agohas been merged