PEFT
Safetensors
GGUF
English
medical
clinical-notes
patient-communication
lora
medgemma
conversational
Instructions to use dejori/note-explain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dejori/note-explain with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use dejori/note-explain with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf dejori/note-explain:Q4_K_M # Run inference directly in the terminal: llama cli -hf dejori/note-explain:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf dejori/note-explain:Q4_K_M # Run inference directly in the terminal: llama cli -hf dejori/note-explain:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf dejori/note-explain:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf dejori/note-explain:Q4_K_M
Use Docker
docker model run hf.co/dejori/note-explain:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use dejori/note-explain with Ollama:
ollama run hf.co/dejori/note-explain:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use dejori/note-explain with Docker Model Runner:
docker model run hf.co/dejori/note-explain:Q4_K_M
- Lemonade
How to use dejori/note-explain with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull dejori/note-explain:Q4_K_M
Run and chat with the model
lemonade run user.note-explain-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Upload gemma-9b-dpo/adapter_config.json with huggingface_hub
Browse files
gemma-9b-dpo/adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "google/gemma-2-9b-it",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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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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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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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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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r": 16,
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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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"q_proj",
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"v_proj",
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"up_proj",
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"o_proj",
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"k_proj",
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"down_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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