Image-Text-to-Text
Transformers
Safetensors
deepseek_v41
text-generation
conversational
8-bit precision
fp8
Instructions to use maletsidibeOS/Anos_AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maletsidibeOS/Anos_AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="maletsidibeOS/Anos_AI") 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 AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("maletsidibeOS/Anos_AI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use maletsidibeOS/Anos_AI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "maletsidibeOS/Anos_AI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "maletsidibeOS/Anos_AI", "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/maletsidibeOS/Anos_AI
- SGLang
How to use maletsidibeOS/Anos_AI 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 "maletsidibeOS/Anos_AI" \ --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": "maletsidibeOS/Anos_AI", "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 "maletsidibeOS/Anos_AI" \ --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": "maletsidibeOS/Anos_AI", "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 maletsidibeOS/Anos_AI with Docker Model Runner:
docker model run hf.co/maletsidibeOS/Anos_AI
Download inference/config.json from maletsidibeOS/Anos_AI: direct link, hf CLI and curl.
- Browser
- Download file 1.98 kB
-
https://huggingface.co/maletsidibeOS/Anos_AI/resolve/main/inference/config.json
- Command line
-
hf download hf://maletsidibeOS/Anos_AI/inference/config.json
-
curl -L -o config.json https://huggingface.co/maletsidibeOS/Anos_AI/resolve/main/inference/config.json
1.98 kB
| { | |
| "vocab_size": 129280, | |
| "dim": 5120, | |
| "moe_inter_dim": 2304, | |
| "n_layers": 40, | |
| "n_mtp_layers": 3, | |
| "dspark_block_size": 5, | |
| "dspark_noise_token_id": 128799, | |
| "dspark_target_layer_ids": [37, 38, 39], | |
| "dspark_markov_rank": 256, | |
| "dspark_n_routed_experts": 128, | |
| "dspark_n_activated_experts": 3, | |
| "n_heads": 64, | |
| "n_routed_experts": 384, | |
| "n_shared_experts": 1, | |
| "n_activated_experts": 6, | |
| "score_func": "sqrtsoftplus", | |
| "route_scale": 1.5, | |
| "swiglu_limit": 10.0, | |
| "q_lora_rank": 1280, | |
| "head_dim": 512, | |
| "rope_head_dim": 64, | |
| "norm_eps": 1e-20, | |
| "o_groups": 8, | |
| "o_lora_rank": 1024, | |
| "window_size": 128, | |
| "kv_source_layers": [2, 8, 14, 20], | |
| "index_source_layers": [2, 8, 14, 20, 24, 28, 32, 36], | |
| "original_seq_len": 65536, | |
| "rope_theta": 10000, | |
| "rope_factor": 16, | |
| "beta_fast": 32, | |
| "beta_slow": 1, | |
| "index_n_heads": 32, | |
| "index_head_dim": 128, | |
| "index_topk": 512, | |
| "candidate_source_layer": 20, | |
| "candidate_topk_blocks": 2048, | |
| "candidate_block_size": 8, | |
| "hc_mult": 4, | |
| "hc_sinkhorn_iters": 20, | |
| "hc_eps": 1e-06, | |
| "engram_layer_ids": [1, 14], | |
| "engram_vocab_size": 16000000, | |
| "engram_num_embeddings": [384006168, 384016682], | |
| "engram_max_ngram_size": 4, | |
| "engram_pad_id": 2, | |
| "engram_compressed_vocab_size": 99092, | |
| "dtype": "fp8", | |
| "expert_dtype": "fp4", | |
| "compress_rope_theta": 160000, | |
| "compress_ratios": [0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0], | |
| "vision_n_layers": 32, | |
| "vision_dim": 1024, | |
| "vision_n_heads": 16, | |
| "vision_inter_dim": 2816, | |
| "vision_patch_size": 14, | |
| "vision_downsample_ratio": 3, | |
| "vision_max_n_token": 1024, | |
| "vision_min_pixels": 295936, | |
| "vision_max_wh_ratio": null, | |
| "image_token_id": 129264, | |
| "engram_n_heads": 8, | |
| "engram_head_dim": 256, | |
| "vision_rope_theta": 10000 | |
| } | |