Image-Text-to-Text
Transformers
Safetensors
English
step3p7
vision-language
multimodal
Mixture of Experts
conversational
custom_code
8-bit precision
modelopt
Instructions to use stepfun-ai/Step-3.7-Flash-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stepfun-ai/Step-3.7-Flash-NVFP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="stepfun-ai/Step-3.7-Flash-NVFP4", trust_remote_code=True) 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("stepfun-ai/Step-3.7-Flash-NVFP4", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("stepfun-ai/Step-3.7-Flash-NVFP4", trust_remote_code=True, 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 stepfun-ai/Step-3.7-Flash-NVFP4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stepfun-ai/Step-3.7-Flash-NVFP4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stepfun-ai/Step-3.7-Flash-NVFP4", "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/stepfun-ai/Step-3.7-Flash-NVFP4
- SGLang
How to use stepfun-ai/Step-3.7-Flash-NVFP4 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 "stepfun-ai/Step-3.7-Flash-NVFP4" \ --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": "stepfun-ai/Step-3.7-Flash-NVFP4", "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 "stepfun-ai/Step-3.7-Flash-NVFP4" \ --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": "stepfun-ai/Step-3.7-Flash-NVFP4", "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 stepfun-ai/Step-3.7-Flash-NVFP4 with Docker Model Runner:
docker model run hf.co/stepfun-ai/Step-3.7-Flash-NVFP4
Add MTP draft layers to NVFP4 checkpoint
Browse filesAdds BF16 MTP draft layers for vLLM speculative decoding and updates safetensors index plus quantization metadata. Original NVFP4 model shards are unchanged.
- config.json +24 -5
- hf_quant_config.json +150 -144
- model-mtp-bf16.safetensors +3 -0
- model.safetensors.index.json +53 -2
config.json
CHANGED
|
@@ -86,7 +86,10 @@
|
|
| 86 |
"sliding_attention",
|
| 87 |
"sliding_attention",
|
| 88 |
"sliding_attention",
|
| 89 |
-
"full_attention"
|
|
|
|
|
|
|
|
|
|
| 90 |
],
|
| 91 |
"max_position_embeddings": 262144,
|
| 92 |
"max_seq_len": 262144,
|
|
@@ -151,7 +154,10 @@
|
|
| 151 |
1.0,
|
| 152 |
1.0,
|
| 153 |
1.0,
|
| 154 |
-
0.5
|
|
|
|
|
|
|
|
|
|
| 155 |
],
|
| 156 |
"rms_norm_eps": 1e-05,
|
| 157 |
"rope_scaling": {
|
|
@@ -259,7 +265,10 @@
|
|
| 259 |
0.0,
|
| 260 |
0.0,
|
| 261 |
7,
|
| 262 |
-
7
|
|
|
|
|
|
|
|
|
|
| 263 |
],
|
| 264 |
"swiglu_limits_shared": [
|
| 265 |
0.0,
|
|
@@ -306,7 +315,10 @@
|
|
| 306 |
0.0,
|
| 307 |
0.0,
|
| 308 |
16,
|
| 309 |
-
16
|
|
|
|
|
|
|
|
|
|
| 310 |
],
|
| 311 |
"torch_dtype": "bfloat16",
|
| 312 |
"use_cache": false,
|
|
@@ -314,6 +326,7 @@
|
|
| 314 |
"use_mfa": false,
|
| 315 |
"use_moe": true,
|
| 316 |
"use_moe_router_bias": true,
|
|
|
|
| 317 |
"use_rope_layers": [],
|
| 318 |
"vocab_size": 128896,
|
| 319 |
"yarn_only_types": [
|
|
@@ -506,7 +519,13 @@
|
|
| 506 |
"model.language_model.layers.9.self_attn*",
|
| 507 |
"model.language_model.layers.9.share_expert*",
|
| 508 |
"model.vision_model*",
|
| 509 |
-
"model.vit_large_projector"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 510 |
],
|
| 511 |
"quant_algo": "NVFP4",
|
| 512 |
"kv_cache_scheme": {
|
|
|
|
| 86 |
"sliding_attention",
|
| 87 |
"sliding_attention",
|
| 88 |
"sliding_attention",
|
| 89 |
+
"full_attention",
|
| 90 |
+
"sliding_attention",
|
| 91 |
+
"sliding_attention",
|
| 92 |
+
"sliding_attention"
|
| 93 |
],
|
| 94 |
"max_position_embeddings": 262144,
|
| 95 |
"max_seq_len": 262144,
|
|
|
|
| 154 |
1.0,
|
| 155 |
1.0,
|
| 156 |
1.0,
|
| 157 |
+
0.5,
|
| 158 |
+
1.0,
|
| 159 |
+
1.0,
|
| 160 |
+
1.0
|
| 161 |
],
|
| 162 |
"rms_norm_eps": 1e-05,
|
| 163 |
"rope_scaling": {
|
|
|
|
| 265 |
0.0,
|
| 266 |
0.0,
|
| 267 |
7,
|
| 268 |
+
7,
|
| 269 |
+
0.0,
|
| 270 |
+
0.0,
|
| 271 |
+
0.0
|
| 272 |
],
|
| 273 |
"swiglu_limits_shared": [
|
| 274 |
0.0,
|
|
|
|
| 315 |
0.0,
|
| 316 |
0.0,
|
| 317 |
16,
|
| 318 |
+
16,
|
| 319 |
+
0.0,
|
| 320 |
+
0.0,
|
| 321 |
+
0.0
|
| 322 |
],
|
| 323 |
"torch_dtype": "bfloat16",
|
| 324 |
"use_cache": false,
|
|
|
|
| 326 |
"use_mfa": false,
|
| 327 |
"use_moe": true,
|
| 328 |
"use_moe_router_bias": true,
|
| 329 |
+
"use_qk_norm": false,
|
| 330 |
"use_rope_layers": [],
|
| 331 |
"vocab_size": 128896,
|
| 332 |
"yarn_only_types": [
|
|
|
|
| 519 |
"model.language_model.layers.9.self_attn*",
|
| 520 |
"model.language_model.layers.9.share_expert*",
|
| 521 |
"model.vision_model*",
|
| 522 |
+
"model.vit_large_projector",
|
| 523 |
+
"model.language_model.layers.45.*",
|
| 524 |
+
"model.language_model.layers.46.*",
|
| 525 |
+
"model.language_model.layers.47.*",
|
| 526 |
+
"model.layers.45.*",
|
| 527 |
+
"model.layers.46.*",
|
| 528 |
+
"model.layers.47.*"
|
| 529 |
],
|
| 530 |
"quant_algo": "NVFP4",
|
| 531 |
"kv_cache_scheme": {
|
hf_quant_config.json
CHANGED
|
@@ -1,145 +1,151 @@
|
|
| 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 |
-
|
| 108 |
-
|
| 109 |
-
|
| 110 |
-
|
| 111 |
-
|
| 112 |
-
|
| 113 |
-
|
| 114 |
-
|
| 115 |
-
|
| 116 |
-
|
| 117 |
-
|
| 118 |
-
|
| 119 |
-
|
| 120 |
-
|
| 121 |
-
|
| 122 |
-
|
| 123 |
-
|
| 124 |
-
|
| 125 |
-
|
| 126 |
-
|
| 127 |
-
|
| 128 |
-
|
| 129 |
-
|
| 130 |
-
|
| 131 |
-
|
| 132 |
-
|
| 133 |
-
|
| 134 |
-
|
| 135 |
-
|
| 136 |
-
|
| 137 |
-
|
| 138 |
-
|
| 139 |
-
|
| 140 |
-
|
| 141 |
-
|
| 142 |
-
|
| 143 |
-
|
| 144 |
-
|
| 145 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
{
|
| 2 |
+
"producer": {
|
| 3 |
+
"name": "modelopt",
|
| 4 |
+
"version": "0.45.0.dev37+g3ad4f4f09.d20260524"
|
| 5 |
+
},
|
| 6 |
+
"quantization": {
|
| 7 |
+
"quant_algo": "NVFP4",
|
| 8 |
+
"kv_cache_quant_algo": "FP8",
|
| 9 |
+
"group_size": 16,
|
| 10 |
+
"exclude_modules": [
|
| 11 |
+
"lm_head",
|
| 12 |
+
"model.language_model.layers.0*",
|
| 13 |
+
"model.language_model.layers.1.*",
|
| 14 |
+
"model.language_model.layers.10.moe.gate",
|
| 15 |
+
"model.language_model.layers.10.self_attn*",
|
| 16 |
+
"model.language_model.layers.10.share_expert*",
|
| 17 |
+
"model.language_model.layers.11.moe.gate",
|
| 18 |
+
"model.language_model.layers.11.self_attn*",
|
| 19 |
+
"model.language_model.layers.11.share_expert*",
|
| 20 |
+
"model.language_model.layers.12.moe.gate",
|
| 21 |
+
"model.language_model.layers.12.self_attn*",
|
| 22 |
+
"model.language_model.layers.12.share_expert*",
|
| 23 |
+
"model.language_model.layers.13.moe.gate",
|
| 24 |
+
"model.language_model.layers.13.self_attn*",
|
| 25 |
+
"model.language_model.layers.13.share_expert*",
|
| 26 |
+
"model.language_model.layers.14.moe.gate",
|
| 27 |
+
"model.language_model.layers.14.self_attn*",
|
| 28 |
+
"model.language_model.layers.14.share_expert*",
|
| 29 |
+
"model.language_model.layers.15.moe.gate",
|
| 30 |
+
"model.language_model.layers.15.self_attn*",
|
| 31 |
+
"model.language_model.layers.15.share_expert*",
|
| 32 |
+
"model.language_model.layers.16.moe.gate",
|
| 33 |
+
"model.language_model.layers.16.self_attn*",
|
| 34 |
+
"model.language_model.layers.16.share_expert*",
|
| 35 |
+
"model.language_model.layers.17.moe.gate",
|
| 36 |
+
"model.language_model.layers.17.self_attn*",
|
| 37 |
+
"model.language_model.layers.17.share_expert*",
|
| 38 |
+
"model.language_model.layers.18.moe.gate",
|
| 39 |
+
"model.language_model.layers.18.self_attn*",
|
| 40 |
+
"model.language_model.layers.18.share_expert*",
|
| 41 |
+
"model.language_model.layers.19.moe.gate",
|
| 42 |
+
"model.language_model.layers.19.self_attn*",
|
| 43 |
+
"model.language_model.layers.19.share_expert*",
|
| 44 |
+
"model.language_model.layers.2.*",
|
| 45 |
+
"model.language_model.layers.20.moe.gate",
|
| 46 |
+
"model.language_model.layers.20.self_attn*",
|
| 47 |
+
"model.language_model.layers.20.share_expert*",
|
| 48 |
+
"model.language_model.layers.21.moe.gate",
|
| 49 |
+
"model.language_model.layers.21.self_attn*",
|
| 50 |
+
"model.language_model.layers.21.share_expert*",
|
| 51 |
+
"model.language_model.layers.22.moe.gate",
|
| 52 |
+
"model.language_model.layers.22.self_attn*",
|
| 53 |
+
"model.language_model.layers.22.share_expert*",
|
| 54 |
+
"model.language_model.layers.23.moe.gate",
|
| 55 |
+
"model.language_model.layers.23.self_attn*",
|
| 56 |
+
"model.language_model.layers.23.share_expert*",
|
| 57 |
+
"model.language_model.layers.24.moe.gate",
|
| 58 |
+
"model.language_model.layers.24.self_attn*",
|
| 59 |
+
"model.language_model.layers.24.share_expert*",
|
| 60 |
+
"model.language_model.layers.25.moe.gate",
|
| 61 |
+
"model.language_model.layers.25.self_attn*",
|
| 62 |
+
"model.language_model.layers.25.share_expert*",
|
| 63 |
+
"model.language_model.layers.26.moe.gate",
|
| 64 |
+
"model.language_model.layers.26.self_attn*",
|
| 65 |
+
"model.language_model.layers.26.share_expert*",
|
| 66 |
+
"model.language_model.layers.27.moe.gate",
|
| 67 |
+
"model.language_model.layers.27.self_attn*",
|
| 68 |
+
"model.language_model.layers.27.share_expert*",
|
| 69 |
+
"model.language_model.layers.28.moe.gate",
|
| 70 |
+
"model.language_model.layers.28.self_attn*",
|
| 71 |
+
"model.language_model.layers.28.share_expert*",
|
| 72 |
+
"model.language_model.layers.29.moe.gate",
|
| 73 |
+
"model.language_model.layers.29.self_attn*",
|
| 74 |
+
"model.language_model.layers.29.share_expert*",
|
| 75 |
+
"model.language_model.layers.3.moe.gate",
|
| 76 |
+
"model.language_model.layers.3.self_attn*",
|
| 77 |
+
"model.language_model.layers.3.share_expert*",
|
| 78 |
+
"model.language_model.layers.30.moe.gate",
|
| 79 |
+
"model.language_model.layers.30.self_attn*",
|
| 80 |
+
"model.language_model.layers.30.share_expert*",
|
| 81 |
+
"model.language_model.layers.31.moe.gate",
|
| 82 |
+
"model.language_model.layers.31.self_attn*",
|
| 83 |
+
"model.language_model.layers.31.share_expert*",
|
| 84 |
+
"model.language_model.layers.32.moe.gate",
|
| 85 |
+
"model.language_model.layers.32.self_attn*",
|
| 86 |
+
"model.language_model.layers.32.share_expert*",
|
| 87 |
+
"model.language_model.layers.33.moe.gate",
|
| 88 |
+
"model.language_model.layers.33.self_attn*",
|
| 89 |
+
"model.language_model.layers.33.share_expert*",
|
| 90 |
+
"model.language_model.layers.34.moe.gate",
|
| 91 |
+
"model.language_model.layers.34.self_attn*",
|
| 92 |
+
"model.language_model.layers.34.share_expert*",
|
| 93 |
+
"model.language_model.layers.35.moe.gate",
|
| 94 |
+
"model.language_model.layers.35.self_attn*",
|
| 95 |
+
"model.language_model.layers.35.share_expert*",
|
| 96 |
+
"model.language_model.layers.36.moe.gate",
|
| 97 |
+
"model.language_model.layers.36.self_attn*",
|
| 98 |
+
"model.language_model.layers.36.share_expert*",
|
| 99 |
+
"model.language_model.layers.37.moe.gate",
|
| 100 |
+
"model.language_model.layers.37.self_attn*",
|
| 101 |
+
"model.language_model.layers.37.share_expert*",
|
| 102 |
+
"model.language_model.layers.38.moe.gate",
|
| 103 |
+
"model.language_model.layers.38.self_attn*",
|
| 104 |
+
"model.language_model.layers.38.share_expert*",
|
| 105 |
+
"model.language_model.layers.39.moe.gate",
|
| 106 |
+
"model.language_model.layers.39.self_attn*",
|
| 107 |
+
"model.language_model.layers.39.share_expert*",
|
| 108 |
+
"model.language_model.layers.4.moe.gate",
|
| 109 |
+
"model.language_model.layers.4.self_attn*",
|
| 110 |
+
"model.language_model.layers.4.share_expert*",
|
| 111 |
+
"model.language_model.layers.40.moe.gate",
|
| 112 |
+
"model.language_model.layers.40.self_attn*",
|
| 113 |
+
"model.language_model.layers.40.share_expert*",
|
| 114 |
+
"model.language_model.layers.41.moe.gate",
|
| 115 |
+
"model.language_model.layers.41.self_attn*",
|
| 116 |
+
"model.language_model.layers.41.share_expert*",
|
| 117 |
+
"model.language_model.layers.42.moe.gate",
|
| 118 |
+
"model.language_model.layers.42.self_attn*",
|
| 119 |
+
"model.language_model.layers.42.share_expert*",
|
| 120 |
+
"model.language_model.layers.43.moe.gate",
|
| 121 |
+
"model.language_model.layers.43.self_attn*",
|
| 122 |
+
"model.language_model.layers.43.share_expert*",
|
| 123 |
+
"model.language_model.layers.44.moe.gate",
|
| 124 |
+
"model.language_model.layers.44.self_attn*",
|
| 125 |
+
"model.language_model.layers.44.share_expert*",
|
| 126 |
+
"model.language_model.layers.5.moe.gate",
|
| 127 |
+
"model.language_model.layers.5.self_attn*",
|
| 128 |
+
"model.language_model.layers.5.share_expert*",
|
| 129 |
+
"model.language_model.layers.6.moe.gate",
|
| 130 |
+
"model.language_model.layers.6.self_attn*",
|
| 131 |
+
"model.language_model.layers.6.share_expert*",
|
| 132 |
+
"model.language_model.layers.7.moe.gate",
|
| 133 |
+
"model.language_model.layers.7.self_attn*",
|
| 134 |
+
"model.language_model.layers.7.share_expert*",
|
| 135 |
+
"model.language_model.layers.8.moe.gate",
|
| 136 |
+
"model.language_model.layers.8.self_attn*",
|
| 137 |
+
"model.language_model.layers.8.share_expert*",
|
| 138 |
+
"model.language_model.layers.9.moe.gate",
|
| 139 |
+
"model.language_model.layers.9.self_attn*",
|
| 140 |
+
"model.language_model.layers.9.share_expert*",
|
| 141 |
+
"model.vision_model*",
|
| 142 |
+
"model.vit_large_projector",
|
| 143 |
+
"model.language_model.layers.45.*",
|
| 144 |
+
"model.language_model.layers.46.*",
|
| 145 |
+
"model.language_model.layers.47.*",
|
| 146 |
+
"model.layers.45.*",
|
| 147 |
+
"model.layers.46.*",
|
| 148 |
+
"model.layers.47.*"
|
| 149 |
+
]
|
| 150 |
+
}
|
| 151 |
+
}
|
model-mtp-bf16.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7af1f8ae0a316de2197c76c0764c8512ff0fb9263a55bb4dfb3f35f25214b7e7
|
| 3 |
+
size 4856347904
|
model.safetensors.index.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"metadata": {
|
| 3 |
"total_parameters": 103810330432,
|
| 4 |
-
"total_size":
|
| 5 |
},
|
| 6 |
"weight_map": {
|
| 7 |
"lm_head.weight": "model-00013-of-00013.safetensors",
|
|
@@ -1891,6 +1891,57 @@
|
|
| 1891 |
"model.vision_model.vit_downsampler1.weight": "model-00001-of-00013.safetensors",
|
| 1892 |
"model.vision_model.vit_downsampler2.bias": "model-00001-of-00013.safetensors",
|
| 1893 |
"model.vision_model.vit_downsampler2.weight": "model-00001-of-00013.safetensors",
|
| 1894 |
-
"model.vit_large_projector.weight": "model-00013-of-00013.safetensors"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1895 |
}
|
| 1896 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"metadata": {
|
| 3 |
"total_parameters": 103810330432,
|
| 4 |
+
"total_size": 129241604232
|
| 5 |
},
|
| 6 |
"weight_map": {
|
| 7 |
"lm_head.weight": "model-00013-of-00013.safetensors",
|
|
|
|
| 1891 |
"model.vision_model.vit_downsampler1.weight": "model-00001-of-00013.safetensors",
|
| 1892 |
"model.vision_model.vit_downsampler2.bias": "model-00001-of-00013.safetensors",
|
| 1893 |
"model.vision_model.vit_downsampler2.weight": "model-00001-of-00013.safetensors",
|
| 1894 |
+
"model.vit_large_projector.weight": "model-00013-of-00013.safetensors",
|
| 1895 |
+
"model.layers.45.eh_proj.weight": "model-mtp-bf16.safetensors",
|
| 1896 |
+
"model.layers.45.enorm.weight": "model-mtp-bf16.safetensors",
|
| 1897 |
+
"model.layers.45.hnorm.weight": "model-mtp-bf16.safetensors",
|
| 1898 |
+
"model.layers.45.input_layernorm.weight": "model-mtp-bf16.safetensors",
|
| 1899 |
+
"model.layers.45.mlp.down_proj.weight": "model-mtp-bf16.safetensors",
|
| 1900 |
+
"model.layers.45.mlp.gate_proj.weight": "model-mtp-bf16.safetensors",
|
| 1901 |
+
"model.layers.45.mlp.up_proj.weight": "model-mtp-bf16.safetensors",
|
| 1902 |
+
"model.layers.45.post_attention_layernorm.weight": "model-mtp-bf16.safetensors",
|
| 1903 |
+
"model.layers.45.self_attn.g_proj.weight": "model-mtp-bf16.safetensors",
|
| 1904 |
+
"model.layers.45.self_attn.k_norm.weight": "model-mtp-bf16.safetensors",
|
| 1905 |
+
"model.layers.45.self_attn.k_proj.weight": "model-mtp-bf16.safetensors",
|
| 1906 |
+
"model.layers.45.self_attn.o_proj.weight": "model-mtp-bf16.safetensors",
|
| 1907 |
+
"model.layers.45.self_attn.q_norm.weight": "model-mtp-bf16.safetensors",
|
| 1908 |
+
"model.layers.45.self_attn.q_proj.weight": "model-mtp-bf16.safetensors",
|
| 1909 |
+
"model.layers.45.self_attn.v_proj.weight": "model-mtp-bf16.safetensors",
|
| 1910 |
+
"model.layers.45.transformer.shared_head.norm.weight": "model-mtp-bf16.safetensors",
|
| 1911 |
+
"model.layers.45.transformer.shared_head.output.weight": "model-mtp-bf16.safetensors",
|
| 1912 |
+
"model.layers.46.eh_proj.weight": "model-mtp-bf16.safetensors",
|
| 1913 |
+
"model.layers.46.enorm.weight": "model-mtp-bf16.safetensors",
|
| 1914 |
+
"model.layers.46.hnorm.weight": "model-mtp-bf16.safetensors",
|
| 1915 |
+
"model.layers.46.input_layernorm.weight": "model-mtp-bf16.safetensors",
|
| 1916 |
+
"model.layers.46.mlp.down_proj.weight": "model-mtp-bf16.safetensors",
|
| 1917 |
+
"model.layers.46.mlp.gate_proj.weight": "model-mtp-bf16.safetensors",
|
| 1918 |
+
"model.layers.46.mlp.up_proj.weight": "model-mtp-bf16.safetensors",
|
| 1919 |
+
"model.layers.46.post_attention_layernorm.weight": "model-mtp-bf16.safetensors",
|
| 1920 |
+
"model.layers.46.self_attn.g_proj.weight": "model-mtp-bf16.safetensors",
|
| 1921 |
+
"model.layers.46.self_attn.k_norm.weight": "model-mtp-bf16.safetensors",
|
| 1922 |
+
"model.layers.46.self_attn.k_proj.weight": "model-mtp-bf16.safetensors",
|
| 1923 |
+
"model.layers.46.self_attn.o_proj.weight": "model-mtp-bf16.safetensors",
|
| 1924 |
+
"model.layers.46.self_attn.q_norm.weight": "model-mtp-bf16.safetensors",
|
| 1925 |
+
"model.layers.46.self_attn.q_proj.weight": "model-mtp-bf16.safetensors",
|
| 1926 |
+
"model.layers.46.self_attn.v_proj.weight": "model-mtp-bf16.safetensors",
|
| 1927 |
+
"model.layers.46.transformer.shared_head.norm.weight": "model-mtp-bf16.safetensors",
|
| 1928 |
+
"model.layers.46.transformer.shared_head.output.weight": "model-mtp-bf16.safetensors",
|
| 1929 |
+
"model.layers.47.eh_proj.weight": "model-mtp-bf16.safetensors",
|
| 1930 |
+
"model.layers.47.enorm.weight": "model-mtp-bf16.safetensors",
|
| 1931 |
+
"model.layers.47.hnorm.weight": "model-mtp-bf16.safetensors",
|
| 1932 |
+
"model.layers.47.input_layernorm.weight": "model-mtp-bf16.safetensors",
|
| 1933 |
+
"model.layers.47.mlp.down_proj.weight": "model-mtp-bf16.safetensors",
|
| 1934 |
+
"model.layers.47.mlp.gate_proj.weight": "model-mtp-bf16.safetensors",
|
| 1935 |
+
"model.layers.47.mlp.up_proj.weight": "model-mtp-bf16.safetensors",
|
| 1936 |
+
"model.layers.47.post_attention_layernorm.weight": "model-mtp-bf16.safetensors",
|
| 1937 |
+
"model.layers.47.self_attn.g_proj.weight": "model-mtp-bf16.safetensors",
|
| 1938 |
+
"model.layers.47.self_attn.k_norm.weight": "model-mtp-bf16.safetensors",
|
| 1939 |
+
"model.layers.47.self_attn.k_proj.weight": "model-mtp-bf16.safetensors",
|
| 1940 |
+
"model.layers.47.self_attn.o_proj.weight": "model-mtp-bf16.safetensors",
|
| 1941 |
+
"model.layers.47.self_attn.q_norm.weight": "model-mtp-bf16.safetensors",
|
| 1942 |
+
"model.layers.47.self_attn.q_proj.weight": "model-mtp-bf16.safetensors",
|
| 1943 |
+
"model.layers.47.self_attn.v_proj.weight": "model-mtp-bf16.safetensors",
|
| 1944 |
+
"model.layers.47.transformer.shared_head.norm.weight": "model-mtp-bf16.safetensors",
|
| 1945 |
+
"model.layers.47.transformer.shared_head.output.weight": "model-mtp-bf16.safetensors"
|
| 1946 |
}
|
| 1947 |
}
|