YAML Metadata Warning: The pipeline tag "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, any-to-any, other

BigCodeLLama 92b GGUF files 🚀

Experimental 92B CodeLlaMA that should be better than stock

Models Merged with base `codellama/CodeLlama-70b-Instruct-hf`

Full model here: https://huggingface.co/nisten/BigCodeLlama-92b

Models Merged

The following models were included in the merge:

../CodeLlama-70b-Python-hf
../CodeLlama-70b-Instruct-hf

Configuration

The following YAML configuration was used to produce this model:

dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 69]
    model:
      model:
        path: ../CodeLlama-70b-Instruct-hf
- sources:
  - layer_range: [42, 80]
    model:
      model:
        path: ../CodeLlama-70b-Python-hf

To merge together the 6bit for example download both parts then do

cat BigCodeLlama-92b-q6.gguf.part0 BigCodeLlama-92b-q6.gguf.part1 > BigCodeLlama-92b-q6.gguf

Comparison over stock with question:

Plan and write code for building a city on mars via calculating aldrin cycler orbits in js for cargo shipments starting in year 2030, and after coding it in python and c++ output a table of calendar of deliver dates.

Don't ask for clarification just do the work smartly.