Model overview
Use this frankenbase for training. Sorry for the mislabelling, the model is a 0.18b 181m parameter, not 0.15. I did not except this repo to blow up and now all the training scripts depend on it. >>[!TIP]🐧 If you're impppatient, get the trained checkpoint file that runs on 1 cpu core: >> >>wget https://huggingface.co/nisten/Biggie-SmoLlm-0.15B-Base/resolve/main/biggie_groked_int8_q8_0.gguf >> >>make sure to install latest llama.cpp first, it's easy on linux & mac: >> >> git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make -j This base model was built one via semi-automated continuous merging to figure out the recipe. Model is more coherent.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。