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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, 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

Mortido/saiga_mistral_7b_lora-F32-GGUF

This LoRA adapter was converted to GGUF format from IlyaGusev/saiga_mistral_7b_lora via the ggml.ai's GGUF-my-lora space. Refer to the original adapter repository for more details.

Use with llama.cpp

# with cli
llama-cli -m base_model.gguf --lora saiga_mistral_7b_lora-f32.gguf (...other args)

# with server
llama-server -m base_model.gguf --lora saiga_mistral_7b_lora-f32.gguf (...other args)

To know more about LoRA usage with llama.cpp server, refer to the llama.cpp server documentation.

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GGUF
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llama

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