No model card content was provided for ElnaggarLab/ankh-base.
Inference Pipeline
template.j2{% set device = "cuda:0" %}
{% set repo_id = "ElnaggarLab/ankh-base" %}
{% set input_text = "Summarize how proteins fold using structural features." %}
{% set max_new_tokens = 256 %}
repo_id = "{{ repo_id }}"
device = "{{ device }}"
input_text = "{{ input_text }}"
max_new_tokens = {{ max_new_tokens }}
from pathlib import Path
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForSeq2SeqLM.from_pretrained(repo_id).to(device)
model.eval()
encoded_inputs = tokenizer(input_text, return_tensors="pt")
encoded_inputs = {key: value.to(device) for key, value in encoded_inputs.items()}
generated_ids = model.generate(**encoded_inputs, max_new_tokens=max_new_tokens)
generated_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
RESULT = {"generated_text": generated_text}
requirements.txt
pipannotated-doc==0.0.4
anyio==4.13.0
certifi==2022.12.7
click==8.3.2
cuda-bindings==12.9.4
cuda-pathfinder==1.2.2
cuda-toolkit==12.8.1
filelock==3.25.2
fsspec==2026.2.0
h11==0.16.0
hf-xet==1.4.3
httpcore==1.0.9
httpx==0.28.1
huggingface-hub==1.10.1
idna==3.4
jinja2==3.1.6
markdown-it-py==4.0.0
markupsafe==3.0.3
mdurl==0.1.2
mpmath==1.3.0
networkx==3.6.1
numpy==2.4.3
nvidia-cublas-cu12==12.8.4.1
nvidia-cuda-cupti-cu12==12.8.90
nvidia-cuda-nvrtc-cu12==12.8.93
nvidia-cuda-runtime-cu12==12.8.90
nvidia-cudnn-cu12==9.19.0.56
nvidia-cufft-cu12==11.3.3.83
nvidia-cufile-cu12==1.13.1.3
nvidia-curand-cu12==10.3.9.90
nvidia-cusolver-cu12==11.7.3.90
nvidia-cusparse-cu12==12.5.8.93
nvidia-cusparselt-cu12==0.7.1
nvidia-nccl-cu12==2.28.9
nvidia-nvjitlink-cu12==12.8.93
nvidia-nvshmem-cu12==3.4.5
nvidia-nvtx-cu12==12.8.90
packaging==24.1
pillow==12.1.1
pygments==2.20.0
pyyaml==6.0.3
regex==2026.4.4
rich==15.0.0
safetensors==0.7.0
sentencepiece==0.2.1
setuptools==70.2.0
shellingham==1.5.4
sympy==1.14.0
tokenizers==0.22.2
torch==2.11.0+cu128
torchaudio==2.11.0+cu128
torchvision==0.26.0+cu128
tqdm==4.66.5
transformers==5.5.4
triton==3.6.0
typer==0.24.1
typing-extensions==4.15.0