Duplicate from crestf411/daybreak-peft
Browse filesCo-authored-by: Crestfall <crestf411@users.noreply.huggingface.co>
- .gitattributes +35 -0
- README.md +5 -0
- command-r-35b/adapter_config.json +34 -0
- command-r-35b/adapter_model.safetensors +3 -0
- llama3-70b/CHANGELOG.txt +3 -0
- llama3-70b/adapter_config.json +34 -0
- llama3-70b/adapter_model.bin +3 -0
- llama3-8b/CHANGELOG.md +2 -0
- llama3-8b/adapter_config.json +34 -0
- llama3-8b/adapter_model.safetensors +3 -0
- mistral-7b/adapter_config.json +32 -0
- mistral-7b/adapter_model.safetensors +3 -0
- mistral-7b/trainer_state.json +0 -0
- mixtral-8x7b/adapter_config.json +33 -0
- mixtral-8x7b/adapter_model.bin +3 -0
- mixtral-8x7b/trainer_state.json +0 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md
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# Daybreak
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This set of LoRAs differ from the crestfall models due to the addition of on-topic SFW content.
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The intention is to produce a more intelligent model that is still capable of niche genre ERP.
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command-r-35b/adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "./curr-model",
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"bias": "none",
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"down_proj",
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"o_proj",
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"v_proj",
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"gate_proj",
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"q_proj",
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"up_proj",
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"k_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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command-r-35b/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:275fd440db994c285e08e01f03bed5f44200c8ebf393f4769e1aca3fa7f4a93c
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size 403777872
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llama3-70b/CHANGELOG.txt
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* 20240525: Pushed v0.4 LoRA, even more deslopping/dataset fixes.
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* 20240521: Pushed v0.3 LoRA, with more deslopping, and dataset fixes. Also uses HQQ quantization instead of QLoRA, which got training up to 8k context size.
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* 20240511: Pushed v0.2 LoRA. Higher context size, and curation/fixes to dataset.
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llama3-70b/adapter_config.json
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{
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"base_model_name_or_path": "",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": false,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [],
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"down_proj",
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"v_proj",
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"k_proj",
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"up_proj",
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"o_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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llama3-70b/adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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size 828891458
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llama3-8b/CHANGELOG.md
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* 2024-04-21: v0.1 release. Merge with base instruct gives poor results.
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* 2024-05-07: v0.2 release. Updated with latest dataset. Merge with non-base instruct gives decent results.
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llama3-8b/adapter_config.json
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"peft_type": "LORA",
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"r": 128,
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"rank_pattern": {},
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"revision": "unsloth",
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"target_modules": [
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"k_proj",
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"o_proj",
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"gate_proj",
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"v_proj",
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"down_proj",
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"up_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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llama3-8b/adapter_model.safetensors
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mistral-7b/adapter_config.json
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"target_modules": [
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"k_proj",
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"down_proj",
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"gate_proj",
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"q_proj",
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"up_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_rslora": false
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}
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mistral-7b/adapter_model.safetensors
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mistral-7b/trainer_state.json
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mixtral-8x7b/adapter_config.json
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"r": 64,
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"target_modules": [
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"w3",
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"w2",
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"w1",
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"gate",
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"o_proj",
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"k_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_rslora": false
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}
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mixtral-8x7b/adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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mixtral-8x7b/trainer_state.json
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