Datasetpublic

dvilasuero/bfcl-kimi

bfcl-kimi Evaluation Results Eval created with evaljobs. This dataset contains evaluation results for the model hf-inference-providers/moonshotai/Kimi-K2-Thinking:fastest using the eval inspect_evals/bfcl from Inspect Evals. To browse the results interactively, visit this Space. How to Run This Eval pip install git+https://github.com/dvsrepo/evaljobs.git export HF_TOKEN=your_token_here evaljobs dvilasuero/bfcl-kimi \ --model <your-model> \ --name <your-name>… See the full description on the dataset page: https://huggingface.co/datasets/dvilasuero/bfcl-kimi.

sourceHugging Faceupdated 10mo agoView on Hugging Face

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bfcl-kimi Evaluation Results

Eval created with evaljobs.

This dataset contains evaluation results for the model hf-inference-providers/moonshotai/Kimi-K2-Thinking:fastest using the eval inspect_evals/bfcl from Inspect Evals.

To browse the results interactively, visit this Space.

How to Run This Eval

bash

pip install git+https://github.com/dvsrepo/evaljobs.git
export HF_TOKEN=your_token_here

evaljobs dvilasuero/bfcl-kimi \
  --model <your-model> \
  --name <your-name> \
  --flavor cpu-basic

Note: For model selection, see the Inspect AI providers documentation. Common examples:

—Hugging Face models: hf/meta-llama/Llama-3.1-8B-Instruct (requires --flavor with GPU, e.g., --flavor t4-medium)
—HF Inference Providers: hf-inference-providers/openai/gpt-oss-120b:fastest (use --flavor cpu-basic or omit)

Splits

—evals: Evaluation runs metadata (one row per evaluation run)
—samples: Sample-level data (one row per sample)

Loading

python

from datasets import load_dataset

evals = load_dataset('dvilasuero/bfcl-kimi', split='evals')
samples = load_dataset('dvilasuero/bfcl-kimi', split='samples')