Instructions to use learn-abc/tinyllama-custom-quotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use learn-abc/tinyllama-custom-quotes with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "learn-abc/tinyllama-custom-quotes") - Transformers
How to use learn-abc/tinyllama-custom-quotes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="learn-abc/tinyllama-custom-quotes") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("learn-abc/tinyllama-custom-quotes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use learn-abc/tinyllama-custom-quotes with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "learn-abc/tinyllama-custom-quotes" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "learn-abc/tinyllama-custom-quotes", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/learn-abc/tinyllama-custom-quotes
- SGLang
How to use learn-abc/tinyllama-custom-quotes 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 "learn-abc/tinyllama-custom-quotes" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "learn-abc/tinyllama-custom-quotes", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "learn-abc/tinyllama-custom-quotes" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "learn-abc/tinyllama-custom-quotes", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use learn-abc/tinyllama-custom-quotes with Docker Model Runner:
docker model run hf.co/learn-abc/tinyllama-custom-quotes
Download checkpoint-200/optimizer.pt from learn-abc/tinyllama-custom-quotes: direct link, hf CLI and curl.
- Browser
- Download file 404 MB
-
https://huggingface.co/learn-abc/tinyllama-custom-quotes/resolve/main/checkpoint-200/optimizer.pt
- Command line
-
hf download hf://learn-abc/tinyllama-custom-quotes/checkpoint-200/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/learn-abc/tinyllama-custom-quotes/resolve/main/checkpoint-200/optimizer.pt
404 MB
- Xet hash:
- 91d4408c716efa3576a448d997a51b625929c9020f3eca91bd71bcc97cfed577
- Size of remote file:
- 404 MB
- SHA256:
- c4fb63f090961479114044f4c55c991fe8beb1901be66e085a6e8cd4fa0bb664
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