jtatman/mistral-trismegistus-7b-gguf

Model Card for Model mistral-trimegistus-7b-gguf

This model repo holds gguf quantized versions of ["teknium/Mistral-Trismegistus-7B"] (https://huggingface.co/teknium/Mistral-Trismegistus-7B).

Model Details

Transcendence is All You Need! Mistral Trismegistus is a model made for people interested in the esoteric, occult, and spiritual.

Model Description

• The First Powerful Occult Expert Model: ~10,000 high quality, deep, rich, instructions on the occult, esoteric, and spiritual.

• Fast: Trained on Mistral, a state of the art 7B parameter model, you can run this model FAST on even a cpu.

• Not a positivity-nazi: This model was trained on all forms of esoteric tasks and knowledge, and is not burdened by the flowery nature of many other models, who chose positivity over creativity.

Model Sources [optional]

All credits go here

Usage

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Training Details

Training Hyperparameters

"_name_or_path": { "desc": null, "value": "mistralai/Mistral-7B-v0.1" }, "architectures": { "desc": null, "value": [ "MistralForCausalLM" ] }, "bad_words_ids": { "desc": null, "value": null }, "bench_dataset": { "desc": null, "value": "pharaouk/dharma-1/dharma_1_mini.json" }, "learning_rate": { "desc": null, "value": 0.0004 }, "max_grad_norm": { "desc": null, "value": 1 }, "fp16_opt_level": { "desc": null, "value": "O1" }, "length_penalty": { "desc": null, "value": 1 }, "max_seq_length": { "desc": null, "value": 4096 }, "sliding_window": { "desc": null, "value": 4096 }, "num_beam_groups": { "desc": null, "value": 1 }, "initializer_range": { "desc": null, "value": 0.02 }, "intermediate_size": { "desc": null, "value": 14336 }, "lr_scheduler_type": { "desc": null, "value": "cosine" }, "num_hidden_layers": { "desc": null, "value": 32 }, "repetition_penalty": { "desc": null, "value": 1 }, "evaluation_strategy": { "desc": null, "value": "steps" }, "num_attention_heads": { "desc": null, "value": 32 }, "num_key_value_heads": { "desc": null, "value": 8 }, "quantization_config": { "desc": null, "value": { "load_in_4bit": true, "load_in_8bit": false, "quant_method": "QuantizationMethod.BITS_AND_BYTES", "llm_int8_threshold": 6, "bnb_4bit_quant_type": "nf4", "llm_int8_skip_modules": null, "bnb_4bit_compute_dtype": "bfloat16", "llm_int8_has_fp16_weight": false, "bnb_4bit_use_double_quant": true, "llm_int8_enable_fp32_cpu_offload": false } }

Speeds, Sizes, Times

{ "_step": 9589, "_wandb.runtime": 12960, "_runtime": 12960.192620515823, "eval/loss": 1.4308836460113523, "train/train_steps_per_second": 0.739, "train/train_samples_per_second": 2.956, "train/loss": 0.3396, "train/epoch": 4, "train/total_flos": 1757020072120942600, "train/train_loss": 0.8929485179171377, "train/learning_rate": 0, "eval/steps_per_second": 2.196, "_timestamp": 1696542775.2713604, "eval/runtime": 11.3829, "train/global_step": 9584, "train/train_runtime": 12962.7813, "eval/samples_per_second": 8.522 }