--- license: apache-2.0 datasets: - qikp/aninsthro - HuggingFaceTB/everyday-conversations-llama3.1-2k language: - en base_model: - cerebras/Cerebras-GPT-111M pipeline_tag: text-generation library_name: transformers new_version: qikp/hummingbird-2.6-110m --- # Hummingbird 🎉 You are looking at Hummingbird 2.5, which largely uses Anthropic's dataset instead! Hummingbird is a Cerebras-GPT derivative trained to be conversational. ## Training The model was trained using the `paged_adamw_8bit` optimizer, gradient checkpointing, 500 steps, 1 batch size, and 4 gradient accumulation steps. ### Datasets The training corpus is made up of: - First 1500 rows of [qikp/aninsthro](https://huggingface.co/datasets/qikp/aninsthro) (a collate of a subset of Anthropic's `hh-rlhf` dataset) - First 500 rows of [HuggingFaceTB/everyday-conversations-llama3.1-2k](https://huggingface.co/datasets/HuggingFaceTB/everyday-conversations-llama3.1-2k) The `train` / `train_sft` splits were used. ### Chat template The Zephyr chat template was used. ## Limitations The model frequently outputs incorrect information, confirmation with a larger, mature model is advised. ## Benchmark This model was benchmarked and compared using embeddings. See the results [here](https://codeberg.org/qikp/benchmarks).