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
File size: 1,515 Bytes
d2fcc73 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | {
"_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
}
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