Instructions to use rasta/BART-FHIR-question with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rasta/BART-FHIR-question with Transformers:

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

pipe = pipeline("text-generation", model="rasta/BART-FHIR-question")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("rasta/BART-FHIR-question")
model = AutoModelForSequenceClassification.from_pretrained("rasta/BART-FHIR-question")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use rasta/BART-FHIR-question with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/rasta/BART-FHIR-question

SGLang

How to use rasta/BART-FHIR-question 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 "rasta/BART-FHIR-question" \
    --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": "rasta/BART-FHIR-question",
		"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 "rasta/BART-FHIR-question" \
        --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": "rasta/BART-FHIR-question",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use rasta/BART-FHIR-question with Docker Model Runner:
```
docker model run hf.co/rasta/BART-FHIR-question
```

rasta commited on Jul 18, 2023

Commit

e2b7649

1 Parent(s): 0b1d8d2

Upload BartForSequenceClassification

Browse files

Files changed (2) hide show

config.json +2 -2
pytorch_model.bin +2 -2

config.json CHANGED Viewed

@@ -1,11 +1,11 @@
 {
-  "_name_or_path": "facebook/bart-large",
   "activation_dropout": 0.1,
   "activation_function": "gelu",
   "add_bias_logits": false,
   "add_final_layer_norm": false,
   "architectures": [
-    "BartForConditionalGeneration"
   ],
   "attention_dropout": 0.1,
   "bos_token_id": 0,

 {
+  "_name_or_path": "rasta/BART-FHIR-question",
   "activation_dropout": 0.1,
   "activation_function": "gelu",
   "add_bias_logits": false,
   "add_final_layer_norm": false,
   "architectures": [
+    "BartForSequenceClassification"
   ],
   "attention_dropout": 0.1,
   "bos_token_id": 0,

pytorch_model.bin CHANGED Viewed

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