PriyanshiD/react_updated_dataset
Viewer • Updated • 231 • 139
How to use PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune", dtype="auto")How to use PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune
How to use PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune" \
--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": "PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune",
"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 "PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune" \
--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": "PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune",
max_seq_length=2048,
)How to use PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune with Docker Model Runner:
docker model run hf.co/PriyanshiD/DeepSeek-R1-Distill-Llama-Finetune
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.