Instructions to use jbenbudd/ptm-llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jbenbudd/ptm-llama with Transformers:

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

pipe = pipeline("text-generation", model="jbenbudd/ptm-llama", device_map="auto")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jbenbudd/ptm-llama")
model = AutoModelForCausalLM.from_pretrained("jbenbudd/ptm-llama", device_map="auto")

PEFT
How to use jbenbudd/ptm-llama with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jbenbudd/ptm-llama with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/jbenbudd/ptm-llama

SGLang

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

Docker Model Runner
How to use jbenbudd/ptm-llama with Docker Model Runner:
```
docker model run hf.co/jbenbudd/ptm-llama
```

ptm-llama / cross_instruction_auc.csv

jbenbudd

Push evaluation artifacts and model card

76652d6 verified 14 days ago

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260 Bytes

	,Methylation,Phosphorylation,Ubiquitination
	Methylation,0.6565676387753249,0.4845552830017262,0.5799763786681202
	Phosphorylation,0.49783048886317616,0.6563748251514029,0.49054773775289695
	Ubiquitination,0.5141878873945271,0.4897625870439934,0.7429060321209946