Text Generation
Transformers
Hindi
English
india
hindi
code-assistant
chat-assistant
instruction-tuned
Eval Results (legacy)
How to use from
SGLangUse 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 "Harshsfd/Bot" \
--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": "Harshsfd/Bot",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
README.md exists but content is empty.
Model tree for Harshsfd/Bot
Base model
mistralai/Mistral-7B-v0.3 Finetuned
mistralai/Mistral-7B-Instruct-v0.3Evaluation results
- Perplexity on OpenHermes (subset)self-reported11.800
- MT-Bench (instruct) on OpenHermes (subset)self-reported7.200
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Harshsfd/Bot" \ --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": "Harshsfd/Bot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'