AI/ML Tooling

133 commands

ollama --version ollama ls ollama pull llama3.2 ollama pull llama3.2:3b ollama pull llama3.2:1b ollama run llama3.2 ollama run llama3.2 'Write a haiku about Linux'ollama run llama3.2 'Return a JSON list of three colors' --format json ollama rm llama3.2 ollama ps ollama stop llama3.2 ollama show llama3.2 ollama show llama3.2 --modelfile ollama cp llama3.2 my-llama-copy ollama create mymodel -f Modelfile ollama create mymodel -q q4_K_M -f Modelfile ollama push myuser/mymodel:latest ollama signin OLLAMA_MODELS=/data/ollama ollama serve curl -s http://localhost:11434/api/tags curl -s http://localhost:11434/api/ps curl -s http://localhost:11434/api/chat -d '{"model":"llama3.2","messages":[{"role":"user","content":"Hi"}]}'curl -s http://localhost:11434/api/generate -d '{"model":"llama3.2","prompt":"Explain Docker in one sentence","stream":false}'hf auth login hf auth login --token $HF_TOKEN hf auth logout hf auth whoami hf auth list hf auth token hf auth switch hf download meta-llama/Llama-3.1-8B-Instruct hf download meta-llama/Llama-3.1-8B-Instruct --include '*.safetensors'hf download sentence-transformers/all-MiniLM-L6-v2 --local-dir ./minilm hf download unsloth/Llama-3.2-1B-Instruct-GGUF --include '*Q4_K_M.gguf' --local-dir ./llama32 hf upload myuser/my-repo ./model.safetensors hf upload myuser/new-repo ./model.safetensors --private hf upload-large-folder myuser/my-repo ./model-weights hf repos create my-llm --type model hf repos create my-secret-model --type model --private hf repos delete myuser/old-model hf repos settings myuser/my-repo --private hf repos move old-namespace/my-model new-namespace/my-model hf cache ls hf cache rm model/gpt2 hf cache prune hf env hf version hf models info meta-llama/Llama-3.2-1B-Instruct hf models ls --sort downloads --limit 10 huggingface-cli login vllm serve meta-llama/Llama-3.1-8B-Instruct vllm serve mistralai/Mistral-7B-Instruct-v0.3 --port 8001 vllm serve meta-llama/Llama-3.1-8B-Instruct --host 0.0.0.0 vllm serve meta-llama/Llama-3.1-8B-Instruct --max-model-len 8192 vllm serve meta-llama/Llama-3.1-8B-Instruct --gpu-memory-utilization 0.9 vllm serve TheBloke/Llama-2-7B-Chat-AWQ --quantization awq vllm serve meta-llama/Llama-3.1-8B-Instruct --tensor-parallel-size 2 vllm serve meta-llama/Llama-3.1-8B-Instruct --served-model-name my-llama vllm serve meta-llama/Llama-3.1-8B-Instruct --api-key sk-my-secret-key vllm serve meta-llama/Llama-3.1-8B-Instruct --dtype float16 vllm serve meta-llama/Llama-3.1-8B-Instruct --enable-auto-tool-choice --tool-call-parser hermes vllm serve meta-llama/Llama-3.1-8B-Instruct --chat-template ./chat_template.jinja vllm serve meta-llama/Llama-3.1-8B-Instruct --max-num-seqs 32 curl -s http://localhost:8000/v1/models | jq '.data[].id'curl -s http://localhost:8000/v1/chat/completions -H 'Content-Type: application/json' -d '{"model":"meta-llama/Llama-3.1-8B-Instruct","messages":[{"role":"user","content":"Hello"}]}'curl -s http://localhost:8000/v1/completions -H 'Content-Type: application/json' -d '{"model":"meta-llama/Llama-3.1-8B-Instruct","prompt":"Once upon a time"}'curl -s http://localhost:8000/health curl -s http://localhost:8000/v1/embeddings -H 'Content-Type: application/json' -d '{"model":"BAAI/bge-small-en-v1.5","input":"Hello world"}'whisper audio.mp3 --model base whisper audio.mp3 --model small --language es whisper audio.mp3 --model medium --output_format txt --output_dir ./transcripts whisper audio.mp3 --model base --task translate whisper audio.mp3 --model tiny --fp16 False whisper audio.mp3 --model base --word_timestamps True whisper audio.mp3 --model base --initial_prompt 'This is a technical podcast about Linux'whisper audio.mp3 --model large-v3 --language en --output_format srt whisper audio.mp3 --model base --beam_size 5 whisper audio.mp3 --model base --output_format all --output_dir ./transcripts lm-eval run --model hf --model_args pretrained=meta-llama/Llama-3.1-8B-Instruct --tasks mmlu --num_fewshot 5 lm-eval run --model hf --model_args pretrained=meta-llama/Llama-3.1-8B-Instruct --tasks truthfulqa_mc2 --device cuda:0 lm-eval run --model vllm --model_args pretrained=meta-llama/Llama-3.1-8B-Instruct,tensor_parallel_size=1 --tasks hellaswag lm-eval run --model hf --model_args pretrained=meta-llama/Llama-3.1-8B-Instruct --tasks gsm8k --apply_chat_template lm-eval run --model hf --model_args pretrained=meta-llama/Llama-3.1-8B-Instruct --tasks hellaswag --limit 100 lm-eval run --model hf --model_args pretrained=meta-llama/Llama-3.1-8B-Instruct --tasks mmlu --output_path ./results/ --log_samples lm-eval run --config my_eval_config.yaml --tasks mmlu lm-eval ls tasks lm-eval ls groups lm-eval validate --tasks hellaswag lm-eval validate --tasks my_custom_task --include_path ./custom_tasks tesseract image.png output tesseract image.png stdout tesseract image.png output -l spa tesseract image.png output -l eng+spa tesseract --list-langs tesseract image.png output --psm 6 tesseract image.png output --oem 1 tesseract image.png output --dpi 300 tesseract image.png output -c tessedit_char_whitelist=0123456789 tesseract image.png output pdf tesseract --version python main.py python main.py --port 8189 python main.py --listen 0.0.0.0 python main.py --cpu python main.py --auto-launch python main.py --output-directory /data/comfy-outputs python main.py --disable-cuda-malloc python main.py --lowvram curl -s http://127.0.0.1:8188/system_stats curl -s http://127.0.0.1:8188/queue | python3 -m json.tool curl -X POST http://127.0.0.1:8188/interrupt curl -X POST http://127.0.0.1:8188/free -H 'Content-Type: application/json' -d '{"unload_models": true, "free_memory": true}'curl -X POST http://127.0.0.1:8188/upload/image -F 'image=@photo.png' -F 'type=input' -F 'overwrite=true'curl -s http://127.0.0.1:8188/object_info | jq 'keys'comfy --version comfy install --nvidia comfy launch --background comfy stop comfy model download --url https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors --relative-path models/checkpoints comfy model list comfy node install comfyui-controlnet-aux comfy node update all curl -fsSL https://ollama.com/install.sh | sh pip install openai-whisper pip install faster-whisper pip install vllm pip install lm-eval pip install huggingface_hub pip install torch pip install transformers sudo apt install tesseract-ocr tesseract-ocr-spa pipx install comfy-cli ct2-transformers-converter --model openai/whisper-large-v3 --output_dir whisper-large-v3-ct2 --quantization float16

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