Instructions to use itsmepv/model_dare_fv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itsmepv/model_dare_fv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="itsmepv/model_dare_fv")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("itsmepv/model_dare_fv") model = AutoModelForCausalLM.from_pretrained("itsmepv/model_dare_fv") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use itsmepv/model_dare_fv with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "itsmepv/model_dare_fv" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "itsmepv/model_dare_fv", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/itsmepv/model_dare_fv
- SGLang
How to use itsmepv/model_dare_fv 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 "itsmepv/model_dare_fv" \ --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": "itsmepv/model_dare_fv", "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 "itsmepv/model_dare_fv" \ --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": "itsmepv/model_dare_fv", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use itsmepv/model_dare_fv with Docker Model Runner:
docker model run hf.co/itsmepv/model_dare_fv
Upload function_vector.pt with huggingface_hub
Browse files- function_vector.pt +3 -0
function_vector.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:94e0fcf7a2f798fdf955c239bd31480e206cebf57d84ab6740e77a83d819222b
|
| 3 |
+
size 4705
|