Instructions to use ramy21/llamamed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ramy21/llamamed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ramy21/llamamed")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ramy21/llamamed") model = AutoModelForCausalLM.from_pretrained("ramy21/llamamed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ramy21/llamamed with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ramy21/llamamed" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ramy21/llamamed", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ramy21/llamamed
- SGLang
How to use ramy21/llamamed with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "ramy21/llamamed" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ramy21/llamamed", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "ramy21/llamamed" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ramy21/llamamed", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ramy21/llamamed with Docker Model Runner:
docker model run hf.co/ramy21/llamamed
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823d50c | 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 | {
"model": "praneshgunner/gpt2-medical-v1",
"project_name": "medgpt",
"data_path": "medgpt/autotrain-data",
"train_split": "train",
"valid_split": null,
"add_eos_token": false,
"block_size": 100,
"model_max_length": 1024,
"trainer": "default",
"use_flash_attention_2": false,
"log": "none",
"disable_gradient_checkpointing": false,
"logging_steps": -1,
"evaluation_strategy": "epoch",
"save_total_limit": 1,
"save_strategy": "epoch",
"auto_find_batch_size": false,
"mixed_precision": null,
"lr": 0.0002,
"epochs": 2,
"batch_size": 4,
"warmup_ratio": 0.1,
"gradient_accumulation": 4,
"optimizer": "adamw_torch",
"scheduler": "linear",
"weight_decay": 0.01,
"max_grad_norm": 1.0,
"seed": 42,
"apply_chat_template": false,
"quantization": null,
"target_modules": null,
"merge_adapter": false,
"peft": false,
"lora_r": 16,
"lora_alpha": 32,
"lora_dropout": 0.05,
"model_ref": null,
"dpo_beta": 0.1,
"prompt_text_column": "autotrain_prompt",
"text_column": "autotrain_text",
"rejected_text_column": "autotrain_rejected_text",
"push_to_hub": true,
"repo_id": "ramy21/llamamed",
"username": null
} |