Instructions to use Jagneshdeveloper/Ekant-14b-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jagneshdeveloper/Ekant-14b-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Jagneshdeveloper/Ekant-14b-small") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Jagneshdeveloper/Ekant-14b-small") model = AutoModelForCausalLM.from_pretrained("Jagneshdeveloper/Ekant-14b-small", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Jagneshdeveloper/Ekant-14b-small with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Jagneshdeveloper/Ekant-14b-small" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jagneshdeveloper/Ekant-14b-small", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Jagneshdeveloper/Ekant-14b-small
- SGLang
How to use Jagneshdeveloper/Ekant-14b-small 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 "Jagneshdeveloper/Ekant-14b-small" \ --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": "Jagneshdeveloper/Ekant-14b-small", "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 "Jagneshdeveloper/Ekant-14b-small" \ --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": "Jagneshdeveloper/Ekant-14b-small", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Jagneshdeveloper/Ekant-14b-small with Docker Model Runner:
docker model run hf.co/Jagneshdeveloper/Ekant-14b-small
server side corruption
The model-10.safetensors file is listed as 123MB in the web page listing, but is realy >600MB. the hf downloader likewise reports:
OSError: Consistency check failed: file should be of size 122597376 but has size 681595600 (model-10.safetensors).
Hey @mradermacher . Thanks for letting me know that model-10.safetensors file is listed as 123MB however it was just a glitch the actual file size was Always 682 I deleted it from here and uploaded it again now it’s fixed you may close the discussion
well, it seems numerous other files are corrupted as well. (I tried to quantize it, but many safetensor files were incomplete)