Text Generation
PEFT
Safetensors
Transformers
aya_vision
image-text-to-text
lora
sft
trl
unsloth
conversational
Instructions to use Jaward/afri-aya-vision-krio-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Jaward/afri-aya-vision-krio-8b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("CohereLabs/aya-vision-8b") model = PeftModel.from_pretrained(base_model, "Jaward/afri-aya-vision-krio-8b") - Transformers
How to use Jaward/afri-aya-vision-krio-8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Jaward/afri-aya-vision-krio-8b") 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)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Jaward/afri-aya-vision-krio-8b") model = AutoModelForMultimodalLM.from_pretrained("Jaward/afri-aya-vision-krio-8b", 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=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Jaward/afri-aya-vision-krio-8b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Jaward/afri-aya-vision-krio-8b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jaward/afri-aya-vision-krio-8b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Jaward/afri-aya-vision-krio-8b
- SGLang
How to use Jaward/afri-aya-vision-krio-8b 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 "Jaward/afri-aya-vision-krio-8b" \ --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": "Jaward/afri-aya-vision-krio-8b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "Jaward/afri-aya-vision-krio-8b" \ --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": "Jaward/afri-aya-vision-krio-8b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio
How to use Jaward/afri-aya-vision-krio-8b with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Jaward/afri-aya-vision-krio-8b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Jaward/afri-aya-vision-krio-8b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Jaward/afri-aya-vision-krio-8b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Jaward/afri-aya-vision-krio-8b", max_seq_length=2048, ) - Docker Model Runner
How to use Jaward/afri-aya-vision-krio-8b with Docker Model Runner:
docker model run hf.co/Jaward/afri-aya-vision-krio-8b
| { | |
| "add_bos_token": true, | |
| "add_eos_token": false, | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<PAD>", | |
| "lstrip": false, | |
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| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
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| "255007": { | |
| "content": "<|CHATBOT_TOKEN|>", | |
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| "255008": { | |
| "content": "<|SYSTEM_TOKEN|>", | |
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| "single_word": false, | |
| "special": false | |
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| "255009": { | |
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| "255010": { | |
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| "content": "<|USER_5_TOKEN|>", | |
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| "single_word": false, | |
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| "content": "<|USER_8_TOKEN|>", | |
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| "single_word": false, | |
| "special": false | |
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| "content": "<|START_RESPONSE|>", | |
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| "special": true | |
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| "content": "<|START_ACTION|>", | |
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| "special": false | |
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| "special": false | |
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| "content": "<|END_TOOL_RESULT|>", | |
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| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "255027": { | |
| "content": "<|EXTRA_8_TOKEN|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
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| "255028": { | |
| "content": "<|NEW_FILE|>", | |
| "lstrip": false, | |
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| "single_word": false, | |
| "special": true | |
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| "255029": { | |
| "content": "<|BEGINNING_OF_PREFIX_FIM_TOKEN|>", | |
| "lstrip": false, | |
| "normalized": false, | |
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| "single_word": false, | |
| "special": false | |
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| "255030": { | |
| "content": "<|BEGINNING_OF_MIDDLE_FIM_TOKEN|>", | |
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| "content": "<|START_OF_IMG|>", | |
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| } | |
| }, | |
| "bos_token": "<BOS_TOKEN>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|END_OF_TURN_TOKEN|>", | |
| "extra_special_tokens": {}, | |
| "legacy": true, | |
| "max_length": null, | |
| "merges_file": null, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<PAD>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "left", | |
| "processor_class": "AyaVisionProcessor", | |
| "sp_model_kwargs": {}, | |
| "spaces_between_special_tokens": false, | |
| "stride": 0, | |
| "tokenizer_class": "CohereTokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": null, | |
| "use_default_system_prompt": false, | |
| "vocab_file": null | |
| } | |