Instructions to use robertmccourt/endoscopy 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 robertmccourt/endoscopy 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 robertmccourt/endoscopy:Q4_0 # Run inference directly in the terminal: llama cli -hf robertmccourt/endoscopy:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf robertmccourt/endoscopy:Q4_0 # Run inference directly in the terminal: llama cli -hf robertmccourt/endoscopy:Q4_0
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 robertmccourt/endoscopy:Q4_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf robertmccourt/endoscopy:Q4_0
Use Docker
docker model run hf.co/robertmccourt/endoscopy:Q4_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use robertmccourt/endoscopy with Ollama:
ollama run hf.co/robertmccourt/endoscopy:Q4_0
- Unsloth Desktop
- Docker Model Runner
How to use robertmccourt/endoscopy with Docker Model Runner:
docker model run hf.co/robertmccourt/endoscopy:Q4_0
- Lemonade
How to use robertmccourt/endoscopy with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull robertmccourt/endoscopy:Q4_0
Run and chat with the model
lemonade run user.endoscopy-Q4_0
List all available models
lemonade list
- Atomic Chat
Download config.json from robertmccourt/endoscopy: direct link, hf CLI and curl.
- Browser
- Download file 1.52 kB
-
https://huggingface.co/robertmccourt/endoscopy/resolve/main/config.json
- Command line
-
hf download hf://robertmccourt/endoscopy/config.json
-
curl -L -o config.json https://huggingface.co/robertmccourt/endoscopy/resolve/main/config.json
1.52 kB
| { | |
| "_name_or_path": "microsoft/llava-med-v1.5-mistral-7b", | |
| "architectures": [ | |
| "LlavaMistralForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "feature_outs": "encoder+decoder", | |
| "freeze_mm_mlp_adapter": false, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "image_aspect_ratio": "square", | |
| "img_size": 640, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 32768, | |
| "mm_hidden_size": 1024, | |
| "mm_patch_merge_type": "flat", | |
| "mm_projector_lr": null, | |
| "mm_projector_type": "mlp2x_gelu", | |
| "mm_use_im_patch_token": false, | |
| "mm_use_im_start_end": false, | |
| "mm_vision_select_feature": "patch", | |
| "mm_vision_select_layer": -2, | |
| "mm_vision_tower": "openai/clip-vit-large-patch14-336", | |
| "model_type": "llava_llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pretraining_tp": 1, | |
| "proj_vis_to_txt_tokens": false, | |
| "prompt_segtok_w_instruct": false, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 1000000.0, | |
| "segtok_posembed": "sincos", | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "tokenizer_model_max_length": 2048, | |
| "tokenizer_padding_side": "right", | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.37.2", | |
| "tune_mm_mlp_adapter": true, | |
| "tune_vision_tokenizer": "none", | |
| "use_cache": true, | |
| "use_mm_proj": true, | |
| "vision_backbone": "convnextlarge", | |
| "vision_tokenizer_lr": null, | |
| "vocab_size": 32000 | |
| } | |