Ivan Yakovlevich Yakovlev
Collection
Collection of models and datasets for imitate a historical figure named Ivan Yakovlevich Yakovlev • 3 items • Updated
How to use evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev")
model = AutoModelForCausalLM.from_pretrained("evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev")How to use evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev
How to use evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev" \
--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": "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev" \
--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": "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev with Docker Model Runner:
docker model run hf.co/evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev
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 "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev" \
--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": "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'No model card
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev" \ --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": "evilfreelancer/ruGPT-3.5-13B-lora-chitchat-yakovlev", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'