Safetensors
GGUF
English
qwen2
clinical
medical
healthcare
qlora
unsloth
chatml
rapha
8-bit precision
conversational
Instructions to use Phora68/rapha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Phora68/rapha 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 Phora68/rapha:Q4_K_M # Run inference directly in the terminal: llama cli -hf Phora68/rapha:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Phora68/rapha:Q4_K_M # Run inference directly in the terminal: llama cli -hf Phora68/rapha: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 Phora68/rapha:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf Phora68/rapha:Q4_K_M
Use Docker
docker model run hf.co/Phora68/rapha:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use Phora68/rapha with Ollama:
ollama run hf.co/Phora68/rapha:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Phora68/rapha with Docker Model Runner:
docker model run hf.co/Phora68/rapha:Q4_K_M
- Lemonade
How to use Phora68/rapha with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Phora68/rapha:Q4_K_M
Run and chat with the model
lemonade run user.rapha-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download adapters/sft_final/adapter_config.json from Phora68/rapha: direct link, hf CLI and curl.
- Browser
- Download file 1.25 kB
-
https://huggingface.co/Phora68/rapha/resolve/main/adapters/sft_final/adapter_config.json
- Command line
-
hf download hf://Phora68/rapha/adapters/sft_final/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/Phora68/rapha/resolve/main/adapters/sft_final/adapter_config.json
1.25 kB
| { | |
| "alora_invocation_tokens": null, | |
| "alpha_pattern": {}, | |
| "arrow_config": null, | |
| "auto_mapping": { | |
| "base_model_class": "Qwen2ForCausalLM", | |
| "parent_library": "transformers.models.qwen2.modeling_qwen2", | |
| "unsloth_fixed": true | |
| }, | |
| "base_model_name_or_path": "unsloth/Qwen2.5-7B-Instruct-bnb-4bit", | |
| "bias": "none", | |
| "corda_config": null, | |
| "ensure_weight_tying": false, | |
| "eva_config": null, | |
| "exclude_modules": null, | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 32, | |
| "lora_bias": false, | |
| "lora_dropout": 0, | |
| "lora_ga_config": null, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "peft_version": "0.19.1", | |
| "qalora_group_size": 16, | |
| "r": 32, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "o_proj", | |
| "q_proj", | |
| "gate_proj", | |
| "v_proj", | |
| "up_proj", | |
| "k_proj", | |
| "down_proj" | |
| ], | |
| "target_parameters": null, | |
| "task_type": "CAUSAL_LM", | |
| "trainable_token_indices": null, | |
| "use_bdlora": null, | |
| "use_dora": false, | |
| "use_qalora": false, | |
| "use_rslora": false | |
| } |