Instructions to use FreedomIntelligence/LongLLaVAMed-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FreedomIntelligence/LongLLaVAMed-9B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="FreedomIntelligence/LongLLaVAMed-9B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/LongLLaVAMed-9B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FreedomIntelligence/LongLLaVAMed-9B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FreedomIntelligence/LongLLaVAMed-9B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/LongLLaVAMed-9B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FreedomIntelligence/LongLLaVAMed-9B

SGLang

How to use FreedomIntelligence/LongLLaVAMed-9B 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 "FreedomIntelligence/LongLLaVAMed-9B" \
    --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": "FreedomIntelligence/LongLLaVAMed-9B",
		"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 "FreedomIntelligence/LongLLaVAMed-9B" \
        --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": "FreedomIntelligence/LongLLaVAMed-9B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FreedomIntelligence/LongLLaVAMed-9B with Docker Model Runner:
```
docker model run hf.co/FreedomIntelligence/LongLLaVAMed-9B
```

LongLLaVAMed-9B

File size: 1,855 Bytes

96bd5fa

{
  "architectures": [
    "LlavaJambaForCausalLM"
  ],
  "attention_dropout": 0.0,
  "attn_layer_offset": 4,
  "attn_layer_period": 8,
  "auto_map": {
    "AutoConfig": "configuration_jamba.JambaConfig",
    "AutoModel": "modeling_jamba.JambaModel",
    "AutoModelForCausalLM": "modeling_jamba.JambaForCausalLM",
    "AutoModelForSequenceClassification": "model.JambaForSequenceClassification"
  },
  "bos_token_id": 1,
  "calc_logits_for_entire_prompt": false,
  "eos_token_id": 2,
  "expert_layer_offset": 1,
  "expert_layer_period": 2,
  "freeze_mm_mlp_adapter": false,
  "hidden_act": "silu",
  "hidden_size": 4096,
  "image_aspect_ratio": "pad",
  "initializer_range": 0.02,
  "intermediate_size": 14336,
  "mamba_conv_bias": true,
  "mamba_d_conv": 4,
  "mamba_d_state": 16,
  "mamba_dt_rank": 256,
  "mamba_expand": 2,
  "mamba_inner_layernorms": true,
  "mamba_proj_bias": false,
  "mm_hidden_size": 1024,
  "mm_patch_merge_type": "flat",
  "mm_projector_lr": null,
  "mm_projector_type": "mlp2x_gelu",
  "mm_use_im_patch_token": false,
  "mm_use_im_start_end": false,
  "mm_vision_select_feature": "patch",
  "mm_vision_select_layer": -2,
  "mm_vision_tower": "openai/clip_vit_large_patch14_336",
  "model_type": "llava_jamba",
  "n_ctx": 262144,
  "num_attention_heads": 32,
  "num_experts": 1,
  "num_experts_per_tok": 1,
  "num_hidden_layers": 32,
  "num_key_value_heads": 8,
  "output_router_logits": false,
  "pad_token_id": 0,
  "resamplePooling": "1d",
  "rms_norm_eps": 1e-06,
  "router_aux_loss_coef": 0.001,
  "sliding_window": null,
  "tie_word_embeddings": false,
  "tokenizer_model_max_length": 40960,
  "tokenizer_padding_side": "right",
  "torch_dtype": "bfloat16",
  "transformers_version": "4.44.2",
  "tune_mm_mlp_adapter": false,
  "use_cache": true,
  "use_mamba_kernels": true,
  "use_mm_proj": true,
  "vocab_size": 65536
}