Text Generation
MLX
Safetensors
qwen3_5_moe
rotorquant
kv-cache-quantization
qwen
qwen-3.6
qwen3.6
Mixture of Experts
quantized
8bit
conversational
8-bit precision
Instructions to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Full-tower republish: 8-bit language tower + BF16 vision tower (fixes mlx_vlm load, discussion #1)
Browse files- PROVENANCE.md +21 -0
- config.json +33 -1
- configuration.json +1 -0
- model-00001-of-00007.safetensors → model-00001-of-00008.safetensors +2 -2
- model-00002-of-00007.safetensors → model-00002-of-00008.safetensors +2 -2
- model-00003-of-00007.safetensors → model-00003-of-00008.safetensors +2 -2
- model-00004-of-00008.safetensors +3 -0
- model-00005-of-00007.safetensors +0 -3
- model-00004-of-00007.safetensors → model-00005-of-00008.safetensors +1 -1
- model-00006-of-00007.safetensors +0 -3
- model-00006-of-00008.safetensors +3 -0
- model-00007-of-00007.safetensors +0 -3
- model-00007-of-00008.safetensors +3 -0
- model-00008-of-00008.safetensors +3 -0
- model.safetensors.index.json +0 -0
- preprocessor_config.json +21 -0
- processor_config.json +50 -0
- tokenizer.json +2 -2
- tokenizer_config.json +3 -2
- video_preprocessor_config.json +21 -0
- vocab.json +0 -0
PROVENANCE.md
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# Provenance
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|---|---|
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| Upstream | [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) @ `995ad96eacd98c81ed38be0c5b274b04031597b0` |
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| Converted | 2026-07-04 |
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| Toolchain | mlx-vlm 0.6.3, mlx 0.31.2, mlx-lm 0.31.3, transformers 5.12.0 |
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| Command | `python -m mlx_vlm convert --hf-path Qwen/Qwen3.6-35B-A3B --revision 995ad96eacd98c81ed38be0c5b274b04031597b0 -q --q-bits 8 --q-group-size 64 --q-mode affine` |
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Contents: language tower quantized (8-bit affine, group size 64) +
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**vision tower in BF16** (333 tensors, unquantized — mlx-vlm skips
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multimodal modules by default). The upstream MTP head is not retained
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(dropped by mlx-vlm sanitize; unused at inference).
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Smoke (pre-publish, Apple Silicon): `mlx_vlm` vision probe and `mlx_lm`
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text probe both passed for this exact payload.
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History: replaces the 2026-04 text-only extraction, which shipped
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without the vision tower and failed to load under `mlx_vlm`
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("Missing 393 parameters"). Reported in discussion #1 on
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majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-4bit.
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config.json
CHANGED
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"architectures": [
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"Qwen3_5MoeForConditionalGeneration"
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],
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"eos_token_id": [
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248046,
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"image_token_id": 248056,
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"model_type": "qwen3_5_moe",
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"quantization": {
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"bits": 8
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}
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},
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"text_config": {
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"attention_bias": false,
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"attention_dropout": 0.0,
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],
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"partial_rotary_factor": 0.25,
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"rope_theta": 10000000,
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-
"
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},
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"router_aux_loss_coef": 0.001,
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"shared_expert_intermediate_size": 512,
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"vocab_size": 248320
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},
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"tie_word_embeddings": false,
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"transformers_version": "4.57.1",
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"video_token_id": 248057,
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"vision_end_token_id": 248054,
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"vision_start_token_id": 248053
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}
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"architectures": [
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"Qwen3_5MoeForConditionalGeneration"
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],
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"do_sample": true,
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"eos_token_id": [
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248046,
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248044
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],
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"generation_config": {
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"bos_token_id": 248044,
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"do_sample": true,
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"eos_token_id": [
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248046,
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248044
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],
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"pad_token_id": 248044,
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"temperature": 1.0,
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"top_k": 20,
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"top_p": 0.95
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},
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"image_token_id": 248056,
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"model_type": "qwen3_5_moe",
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"quantization": {
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"bits": 8
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}
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},
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"temperature": 1.0,
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"text_config": {
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"attention_bias": false,
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"attention_dropout": 0.0,
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],
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"partial_rotary_factor": 0.25,
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"rope_theta": 10000000,
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"rope_type": "default"
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},
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"router_aux_loss_coef": 0.001,
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"shared_expert_intermediate_size": 512,
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"vocab_size": 248320
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},
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"tie_word_embeddings": false,
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"top_k": 20,
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"top_p": 0.95,
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"transformers_version": "4.57.1",
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"video_token_id": 248057,
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"vision_config": {
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"deepstack_visual_indexes": [],
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"depth": 27,
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"hidden_act": "gelu_pytorch_tanh",
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"hidden_size": 1152,
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"in_channels": 3,
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"initializer_range": 0.02,
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"intermediate_size": 4304,
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"model_type": "qwen3_5_moe",
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"num_heads": 16,
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"num_position_embeddings": 2304,
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"out_hidden_size": 2048,
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"patch_size": 16,
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"spatial_merge_size": 2,
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"temporal_patch_size": 2
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},
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"vision_end_token_id": 248054,
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"vision_start_token_id": 248053
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}
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configuration.json
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{"framework":"Pytorch","task":"visual-question-answering"}
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model.safetensors.index.json
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preprocessor_config.json
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{
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"size": {
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"longest_edge": 16777216,
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"shortest_edge": 65536
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},
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"patch_size": 16,
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"temporal_patch_size": 2,
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"merge_size": 2,
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"image_mean": [
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0.5,
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"image_std": [
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],
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"processor_class": "Qwen3VLProcessor",
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"image_processor_type": "Qwen2VLImageProcessorFast"
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}
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processor_config.json
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"image_processor": {
|
| 3 |
+
"do_convert_rgb": true,
|
| 4 |
+
"do_normalize": true,
|
| 5 |
+
"do_rescale": true,
|
| 6 |
+
"image_mean": [
|
| 7 |
+
0.5,
|
| 8 |
+
0.5,
|
| 9 |
+
0.5
|
| 10 |
+
],
|
| 11 |
+
"image_processor_type": "Qwen3VLImageProcessor",
|
| 12 |
+
"image_std": [
|
| 13 |
+
0.5,
|
| 14 |
+
0.5,
|
| 15 |
+
0.5
|
| 16 |
+
],
|
| 17 |
+
"max_pixels": 16777216,
|
| 18 |
+
"merge_size": 2,
|
| 19 |
+
"min_pixels": 65536,
|
| 20 |
+
"patch_size": 16,
|
| 21 |
+
"rescale_factor": 0.00392156862745098,
|
| 22 |
+
"temporal_patch_size": 2
|
| 23 |
+
},
|
| 24 |
+
"processor_class": "Qwen3VLProcessor",
|
| 25 |
+
"video_processor": {
|
| 26 |
+
"do_convert_rgb": true,
|
| 27 |
+
"do_normalize": true,
|
| 28 |
+
"do_rescale": true,
|
| 29 |
+
"fps": 2.0,
|
| 30 |
+
"image_mean": [
|
| 31 |
+
0.5,
|
| 32 |
+
0.5,
|
| 33 |
+
0.5
|
| 34 |
+
],
|
| 35 |
+
"image_std": [
|
| 36 |
+
0.5,
|
| 37 |
+
0.5,
|
| 38 |
+
0.5
|
| 39 |
+
],
|
| 40 |
+
"max_frames": 768,
|
| 41 |
+
"max_pixels": 25165824,
|
| 42 |
+
"merge_size": 2,
|
| 43 |
+
"min_frames": 4,
|
| 44 |
+
"min_pixels": 4096,
|
| 45 |
+
"patch_size": 16,
|
| 46 |
+
"rescale_factor": 0.00392156862745098,
|
| 47 |
+
"temporal_patch_size": 2,
|
| 48 |
+
"video_processor_type": "Qwen3VLVideoProcessor"
|
| 49 |
+
}
|
| 50 |
+
}
|
tokenizer.json
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
|
| 3 |
+
size 19989325
|
tokenizer_config.json
CHANGED
|
@@ -10,6 +10,7 @@
|
|
| 10 |
"errors": "replace",
|
| 11 |
"image_token": "<|image_pad|>",
|
| 12 |
"is_local": true,
|
|
|
|
| 13 |
"model_max_length": 262144,
|
| 14 |
"model_specific_special_tokens": {
|
| 15 |
"audio_bos_token": "<|audio_start|>",
|
|
@@ -22,9 +23,9 @@
|
|
| 22 |
},
|
| 23 |
"pad_token": "<|endoftext|>",
|
| 24 |
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
|
|
|
| 25 |
"split_special_tokens": false,
|
| 26 |
-
"tokenizer_class": "
|
| 27 |
-
"tool_parser_type": "qwen3_coder",
|
| 28 |
"unk_token": null,
|
| 29 |
"video_token": "<|video_pad|>",
|
| 30 |
"vision_bos_token": "<|vision_start|>",
|
|
|
|
| 10 |
"errors": "replace",
|
| 11 |
"image_token": "<|image_pad|>",
|
| 12 |
"is_local": true,
|
| 13 |
+
"local_files_only": false,
|
| 14 |
"model_max_length": 262144,
|
| 15 |
"model_specific_special_tokens": {
|
| 16 |
"audio_bos_token": "<|audio_start|>",
|
|
|
|
| 23 |
},
|
| 24 |
"pad_token": "<|endoftext|>",
|
| 25 |
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 26 |
+
"processor_class": "Qwen3VLProcessor",
|
| 27 |
"split_special_tokens": false,
|
| 28 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
|
|
|
| 29 |
"unk_token": null,
|
| 30 |
"video_token": "<|video_pad|>",
|
| 31 |
"vision_bos_token": "<|vision_start|>",
|
video_preprocessor_config.json
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"size": {
|
| 3 |
+
"longest_edge": 25165824,
|
| 4 |
+
"shortest_edge": 4096
|
| 5 |
+
},
|
| 6 |
+
"patch_size": 16,
|
| 7 |
+
"temporal_patch_size": 2,
|
| 8 |
+
"merge_size": 2,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.5,
|
| 16 |
+
0.5,
|
| 17 |
+
0.5
|
| 18 |
+
],
|
| 19 |
+
"processor_class": "Qwen3VLProcessor",
|
| 20 |
+
"video_processor_type": "Qwen3VLVideoProcessor"
|
| 21 |
+
}
|
vocab.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|