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
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -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/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -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
- LM Studio
- Jan
- Ollama
How to use Phora68/rapha with Ollama:
ollama run hf.co/Phora68/rapha:Q4_K_M
- Unsloth Studio
How to use Phora68/rapha with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Phora68/rapha to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Phora68/rapha to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Phora68/rapha to start chatting
- 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
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- config.json +83 -0
- generation_config.json +14 -0
- model.safetensors +3 -0
config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": null,
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"dtype": "bfloat16",
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 70,
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"model_type": "qwen2",
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"num_attention_heads": 16,
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"num_hidden_layers": 36,
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"num_key_value_heads": 2,
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"pad_token_id": 151654,
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"quantization_config": {
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"bnb_4bit_compute_dtype": "bfloat16",
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"bnb_4bit_quant_type": "nf4",
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"bnb_4bit_use_double_quant": true,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_has_fp16_weight": false,
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"llm_int8_skip_modules": null,
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"llm_int8_threshold": 6.0,
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"load_in_4bit": true,
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"load_in_8bit": false,
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"quant_method": "bitsandbytes"
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},
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 1000000.0,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "5.5.0",
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"unsloth_fixed": true,
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"unsloth_version": "2026.7.4",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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{
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"max_length": 32768,
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"pad_token_id": 151654,
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"repetition_penalty": 1.05,
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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"transformers_version": "5.5.0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:dacc7d9e174c92b4b26a0976502dccb78b36991d3d52db8eb36f59249104817d
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size 2054625562
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