Instructions to use lumierenoir/klev-0.8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lumierenoir/klev-0.8b with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Install section: pip install klev
Browse files
README.md
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Probe hyperparameters (in `stitch/probe-*.pt`): TweetEval `T = 105.19`, `beta = 16.0`,
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`ext_weight = 1.0`; RumourEval `T = 1305.8`, `beta = 16.0`, `ext_weight = 1.0`.
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## Usage
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klev is a **library first**. A decision model is small and stateless, so the normal way to use
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Probe hyperparameters (in `stitch/probe-*.pt`): TweetEval `T = 105.19`, `beta = 16.0`,
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`ext_weight = 1.0`; RumourEval `T = 1305.8`, `beta = 16.0`, `ext_weight = 1.0`.
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## Install
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```bash
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pip install klev
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```
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`klev` is the library: it carries the loader, the pointer readout, the record format and both
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usage paths, so a consumer does not clone this repo to use a checkpoint. Two version floors
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matter and pip does not know they are related to the architecture:
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| | why |
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| `transformers >= 5.5.0` | the `qwen3_5` and `gemma4` architectures do not exist before it. On 5.3.0 `AutoConfig` raises "Transformers does not recognize this architecture", which unsloth then **misreports** as a generic "not supported yet" ValueError — it reads like a missing model, not a version. |
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| `unsloth >= 2026.9.11` | first release carrying gemma4 support. |
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Install unsloth with `--no-deps` if you are on ROCm, so its CUDA `xformers` dependency does not
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replace your ROCm torch build.
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On AMD/ROCm also `source scripts/rocm_env.sh` from the repo (shipped in the wheel as
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`klev.scripts`) **before** importing — it sets the arch override, `TORCH_ROCM_AOTRITON_ENABLE_BF16=0`,
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`UNSLOTH_COMPILE_DISABLE=1` and the rest. All of it is load-bearing; see
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`docs/m11-qwen35-08b.md`.
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Two console scripts come with it:
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```bash
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klev-system-one --ckpt lumierenoir/klev-0.8b --request my_request.json # no server
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klev-serve --ckpt lumierenoir/klev-0.8b --port 8090 # optional HTTP
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```
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`load_klev()` reads the base model from the checkpoint's own `adapter_config.json` and picks the
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matching delimiters, so you do not have to pass `base=` or `preset=`. Pairing a checkpoint with
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another model's weights would otherwise be silent nonsense rather than an error.
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## Usage
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klev is a **library first**. A decision model is small and stateless, so the normal way to use
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