Image-Text-to-Text
Transformers
Safetensors
qwen3_5
fara
computer-use
browser-automation
dom
baseline
evaluation
reproducibility
conversational
Instructions to use WootzappLab/fara-9b-baseline-eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WootzappLab/fara-9b-baseline-eval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="WootzappLab/fara-9b-baseline-eval") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("WootzappLab/fara-9b-baseline-eval") model = AutoModelForMultimodalLM.from_pretrained("WootzappLab/fara-9b-baseline-eval", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use WootzappLab/fara-9b-baseline-eval with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "WootzappLab/fara-9b-baseline-eval" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WootzappLab/fara-9b-baseline-eval", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/WootzappLab/fara-9b-baseline-eval
- SGLang
How to use WootzappLab/fara-9b-baseline-eval 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 "WootzappLab/fara-9b-baseline-eval" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WootzappLab/fara-9b-baseline-eval", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "WootzappLab/fara-9b-baseline-eval" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WootzappLab/fara-9b-baseline-eval", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use WootzappLab/fara-9b-baseline-eval with Docker Model Runner:
docker model run hf.co/WootzappLab/fara-9b-baseline-eval
File size: 3,287 Bytes
ee94639 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | {
"schema_version": 1,
"source_repository": "microsoft/Fara1.5-9B",
"source_revision": "1a93677cd89d5601bc2ed759791e981f3a520032",
"destination_repository": "WootzappLab/fara-9b-baseline-eval",
"weights_modified": false,
"source_file_count_excluding_replaced_model_card": 16,
"files": [
{
"path": ".gitattributes",
"size": 1570,
"git_blob_sha1": "52373fe24473b1aa44333d318f578ae6bf04b49b",
"lfs_sha256": null
},
{
"path": "chat_template.jinja",
"size": 7756,
"git_blob_sha1": "a585dec894e63da457d9440ec6aa7caa16d20860",
"lfs_sha256": null
},
{
"path": "config.json",
"size": 2807,
"git_blob_sha1": "d4d0e89002b9f3c9d2c31f36a601eaaecaf61fb5",
"lfs_sha256": null
},
{
"path": "generation_config.json",
"size": 115,
"git_blob_sha1": "11dd07a690ead29d7b43bad06c3c5d6bbf644fcf",
"lfs_sha256": null
},
{
"path": "merges.txt",
"size": 3353259,
"git_blob_sha1": "a494e019ca1502219fd0128658b979e5f05ae8e8",
"lfs_sha256": null
},
{
"path": "model-00001-of-00004.safetensors",
"size": 5933189920,
"git_blob_sha1": "c563861fa4fde0742a756dc162a472100ab31721",
"lfs_sha256": "67f3a84141ad12848faf30cb44092278d36a2bebf66b9c2214295717c8cc9256"
},
{
"path": "model-00002-of-00004.safetensors",
"size": 5996214640,
"git_blob_sha1": "796fda0736e0adf5fa4d7f7a6c09254f4dc9ee49",
"lfs_sha256": "7423a1eed832f0c19da128565cff02091866ac0716fa75cb729b37408409799a"
},
{
"path": "model-00003-of-00004.safetensors",
"size": 5998812040,
"git_blob_sha1": "65cc15a5148494792bd18346751d7536689bd771",
"lfs_sha256": "a1326ed603b39fe7cd6f95a385648d9ff2abebcf44a725aead1b49cdf25836db"
},
{
"path": "model-00004-of-00004.safetensors",
"size": 891503832,
"git_blob_sha1": "feaed0ac434dd654aeb9998856126a3fb8cca5aa",
"lfs_sha256": "8db40d4df27a0bb90baf3eff67e47c54d83b652543ad2246c8f7482f3b194470"
},
{
"path": "model.safetensors.index.json",
"size": 69253,
"git_blob_sha1": "827eb80573d3ce164b1d2565a6e8bb3da93e84b4",
"lfs_sha256": null
},
{
"path": "preprocessor_config.json",
"size": 390,
"git_blob_sha1": "2ea84a437d448ff71b08df68fdd949d5cc4ebb64",
"lfs_sha256": null
},
{
"path": "processor_config.json",
"size": 1190,
"git_blob_sha1": "e6c966185429c0c7af282c60d570b6436e618471",
"lfs_sha256": null
},
{
"path": "tokenizer.json",
"size": 19989343,
"git_blob_sha1": "67741b04f23bfdb46501f748ce27865ec82eccfb",
"lfs_sha256": "87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4"
},
{
"path": "tokenizer_config.json",
"size": 1183,
"git_blob_sha1": "20740fa45e655c49d1f5290734c4b5e26be4cc2f",
"lfs_sha256": null
},
{
"path": "video_preprocessor_config.json",
"size": 385,
"git_blob_sha1": "3ba673a5ad7d4d13f54155ecd38b2a94a6dac8fe",
"lfs_sha256": null
},
{
"path": "vocab.json",
"size": 6722759,
"git_blob_sha1": "0aa0ce0658d60ac4a5d609f4eadb0e8e43514176",
"lfs_sha256": null
}
]
}
|