Instructions to use google/translategemma-4b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/translategemma-4b-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="google/translategemma-4b-it")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/translategemma-4b-it", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use google/translategemma-4b-it with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/translategemma-4b-it" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/translategemma-4b-it", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/translategemma-4b-it
- SGLang
How to use google/translategemma-4b-it 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 "google/translategemma-4b-it" \ --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": "google/translategemma-4b-it", "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 "google/translategemma-4b-it" \ --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": "google/translategemma-4b-it", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/translategemma-4b-it with Docker Model Runner:
docker model run hf.co/google/translategemma-4b-it
Cannot load processor with `AutoProcessor` from transformers ≥ 5.4.0
#20
by haukelicht - opened
With transformers≥5.4.0, running
from transformers import AutoProcessor
processor = AutoProcessor.from_pretrained("google/translategemma-4b-it")
raises the following error:
ValueError: Unrecognized image processor in google/translategemma-4b-it. Should have a `image_processor_type` key in its preprocessor_config.json of config.json, or one of the following `model_type` keys in its config.json: aimv2, aimv2_vision_model, align, altclip, aria, aya_vision, beit, bit, blip, blip-2, bridgetower, chameleon, chinese_clip, chmv2, clip, clipseg, cohere2_vision, colpali, colqwen2, conditional_detr, convnext, convnextv2, cvt, data2vec-vision, deepseek_vl, deepseek_vl_hybrid, deformable_detr, deit, depth_anything, depth_pro, detr, dinat, dinov2, dinov3_vit, donut-swin, dpt, edgetam, efficientloftr, efficientnet, emu3, eomt, eomt_dinov3, ernie4_5_vl_moe, flava, florence2, focalnet, fuyu, gemma3, gemma3n, git, glm46v, glm4v, glm_image, glpn, got_ocr2, grounding-dino, groupvit, hiera, idefics, idefics2, idefics3, ijepa, imagegpt, instructblip, internvl, janus, kosmos-2, kosmos-2.5, layoutlmv2, layoutlmv3, layoutxlm, levit, lfm2_vl, lightglue, lighton_ocr, llama4, llava, llava_next, llava_next_video, llava_onevision, lw_detr, mask2former, maskformer, metaclip_2, mgp-str, mistral3, mlcd, mllama, mm-grounding-dino, mobilenet_v1, mobilenet_v2, mobilevit, mobilevitv2, nougat, omdet-turbo, oneformer, ovis2, owlv2, owlvit, paddleocr_vl, paligemma, perceiver, perception_lm, phi4_multimodal, pi0, pix2struct, pixio, pixtral, poolformer, pp_chart2table, pp_doclayout_v2, pp_doclayout_v3, pp_lcnet, pp_ocrv5_mobile_det, pp_ocrv5_mobile_rec, pp_ocrv5_server_det, pp_ocrv5_server_rec, prompt_depth_anything, pvt, pvt_v2, qwen2_5_omni, qwen2_5_vl, qwen2_vl, qwen3_5, qwen3_5_moe, qwen3_omni_moe, qwen3_vl, regnet, resnet, rt_detr, sam, sam2, sam2_video, sam3, sam3_tracker, sam3_tracker_video, sam3_video, sam_hq, segformer, seggpt, shieldgemma2, siglip, siglip2, slanext, smolvlm, superglue, superpoint, swiftformer, swin, swin2sr, swinv2, t5gemma2, t5gemma2_encoder, table-transformer, textnet, timesformer, timm_wrapper, trocr, tvp, udop, upernet, uvdoc, video_llama_3, video_llava, videomae, vilt, vipllava, vit, vit_mae, vit_msn, vitmatte, vitpose, xclip, yolos, zoedepth
Solution
Downgrade transformers to version 5.3.0
haukelicht changed discussion title from Cannot load processor with `AutoProcessor` from transformers ≥ 5.4.0 and higher to Cannot load processor with `AutoProcessor` from transformers ≥ 5.4.0