Instructions to use leslyarun/bloom_ncbi_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use leslyarun/bloom_ncbi_finetuned with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="leslyarun/bloom_ncbi_finetuned")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("leslyarun/bloom_ncbi_finetuned")
model = AutoModelForCausalLM.from_pretrained("leslyarun/bloom_ncbi_finetuned", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use leslyarun/bloom_ncbi_finetuned with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "leslyarun/bloom_ncbi_finetuned"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "leslyarun/bloom_ncbi_finetuned",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/leslyarun/bloom_ncbi_finetuned

SGLang

How to use leslyarun/bloom_ncbi_finetuned 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 "leslyarun/bloom_ncbi_finetuned" \
    --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": "leslyarun/bloom_ncbi_finetuned",
		"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 "leslyarun/bloom_ncbi_finetuned" \
        --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": "leslyarun/bloom_ncbi_finetuned",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use leslyarun/bloom_ncbi_finetuned with Docker Model Runner:
```
docker model run hf.co/leslyarun/bloom_ncbi_finetuned
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Bloom Model finetuned on the NCBI disease dataset to generate synthetic data similar to the NCBI disease dataset.

Downloads last month: 12

Safetensors

Model size

1B params

Tensor type

F32

Model tree for leslyarun/bloom_ncbi_finetuned

Quantizations

2 models

leslyarun
/

bloom_ncbi_finetuned

Bloom Model finetuned on the NCBI disease dataset to generate synthetic data similar to the NCBI disease dataset.

Model tree for leslyarun/bloom_ncbi_finetuned

Dataset used to train leslyarun/bloom_ncbi_finetuned