Instructions to use 2026hbk/endtoendvisionlanguagemodelfinetunedtutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 2026hbk/endtoendvisionlanguagemodelfinetunedtutorial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="2026hbk/endtoendvisionlanguagemodelfinetunedtutorial") 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, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("2026hbk/endtoendvisionlanguagemodelfinetunedtutorial") model = AutoModelForImageTextToText.from_pretrained("2026hbk/endtoendvisionlanguagemodelfinetunedtutorial") 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 2026hbk/endtoendvisionlanguagemodelfinetunedtutorial with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "2026hbk/endtoendvisionlanguagemodelfinetunedtutorial" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "2026hbk/endtoendvisionlanguagemodelfinetunedtutorial", "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/2026hbk/endtoendvisionlanguagemodelfinetunedtutorial
- SGLang
How to use 2026hbk/endtoendvisionlanguagemodelfinetunedtutorial 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 "2026hbk/endtoendvisionlanguagemodelfinetunedtutorial" \ --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": "2026hbk/endtoendvisionlanguagemodelfinetunedtutorial", "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 "2026hbk/endtoendvisionlanguagemodelfinetunedtutorial" \ --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": "2026hbk/endtoendvisionlanguagemodelfinetunedtutorial", "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 2026hbk/endtoendvisionlanguagemodelfinetunedtutorial with Docker Model Runner:
docker model run hf.co/2026hbk/endtoendvisionlanguagemodelfinetunedtutorial
Upload 9 files
Browse files- README.md +58 -0
- chat_template.jinja +2 -0
- config.json +164 -0
- generation_config.json +10 -0
- model.safetensors +3 -0
- processor_config.json +79 -0
- tokenizer.json +0 -0
- tokenizer_config.json +31 -0
- training_args.bin +3 -0
README.md
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---
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base_model: HuggingFaceTB/SmolVLM2-500M-Video-Instruct
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library_name: transformers
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model_name: vlmfu
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tags:
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- generated_from_trainer
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- trl
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- sft
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licence: license
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---
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# Model Card for vlmfu
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This model is a fine-tuned version of [HuggingFaceTB/SmolVLM2-500M-Video-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM2-500M-Video-Instruct).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="None", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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This model was trained with SFT.
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### Framework versions
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- TRL: 0.27.1
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- Transformers: 5.0.0
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- Pytorch: 2.10.0+cu129
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- Datasets: 4.5.0
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- Tokenizers: 0.22.2
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## Citations
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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chat_template.jinja
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<|im_start|>{% for message in messages %}{{message['role'] | capitalize}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}{% if line['type'] == 'text' %}{{line['text']}}{% elif line['type'] == 'image' %}{{ '<image>' }}{% endif %}{% endfor %}<end_of_utterance>
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{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}
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config.json
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{
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"architectures": [
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"SmolVLMForConditionalGeneration"
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],
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"bos_token_id": 1,
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"dtype": "bfloat16",
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"eos_token_id": 49279,
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"image_token_id": 49190,
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"model_type": "smolvlm",
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"pad_token_id": 2,
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"scale_factor": 4,
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"text_config": {
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"_flash_attn_2_enabled": true,
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"_name_or_path": "None",
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"architectures": [
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"VLlama3ForCausalLM"
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],
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"attention_bias": false,
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| 19 |
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"attention_dropout": 0.0,
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| 20 |
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"bos_token_id": 1,
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| 21 |
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"dtype": "bfloat16",
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| 22 |
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"eos_token_id": 2,
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| 23 |
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"head_dim": 64,
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| 24 |
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"hidden_act": "silu",
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| 25 |
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"hidden_size": 960,
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| 26 |
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"initializer_range": 0.02,
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| 27 |
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"intermediate_size": 2560,
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| 28 |
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"is_llama_config": true,
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| 29 |
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"max_position_embeddings": 8192,
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| 30 |
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"mlp_bias": false,
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| 31 |
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"model_type": "llama",
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| 32 |
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"neftune_noise_alpha": 0.0,
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| 33 |
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"num_attention_heads": 15,
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| 34 |
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"num_hidden_layers": 32,
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| 35 |
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"num_key_value_heads": 5,
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| 36 |
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"pad_token_id": 2,
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| 37 |
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"perceiver_config": {
|
| 38 |
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"_attn_implementation_autoset": false,
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| 39 |
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"_name_or_path": "",
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| 40 |
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"add_cross_attention": false,
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| 41 |
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"architectures": null,
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| 42 |
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"attention_dropout": 0.0,
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| 43 |
+
"bad_words_ids": null,
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| 44 |
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"begin_suppress_tokens": null,
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| 45 |
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"bos_token_id": null,
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| 46 |
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"chunk_size_feed_forward": 0,
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| 47 |
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"cross_attention_hidden_size": null,
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| 48 |
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"decoder_start_token_id": null,
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| 49 |
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"diversity_penalty": 0.0,
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| 50 |
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"do_sample": false,
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| 51 |
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"early_stopping": false,
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| 52 |
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"encoder_no_repeat_ngram_size": 0,
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| 53 |
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"eos_token_id": null,
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| 54 |
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"exponential_decay_length_penalty": null,
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| 55 |
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"finetuning_task": null,
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| 56 |
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"forced_bos_token_id": null,
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| 57 |
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"forced_eos_token_id": null,
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| 58 |
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"hidden_act": "silu",
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"id2label": {
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"0": "LABEL_0",
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| 61 |
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"1": "LABEL_1"
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| 62 |
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},
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| 63 |
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"is_decoder": false,
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| 64 |
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"is_encoder_decoder": false,
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| 65 |
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"label2id": {
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| 66 |
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"LABEL_0": 0,
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| 67 |
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"LABEL_1": 1
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| 68 |
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},
|
| 69 |
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"length_penalty": 1.0,
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| 70 |
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"max_length": 20,
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| 71 |
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"min_length": 0,
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| 72 |
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"model_type": "vllama3",
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| 73 |
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"no_repeat_ngram_size": 0,
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| 74 |
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"num_beam_groups": 1,
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| 75 |
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"num_beams": 1,
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| 76 |
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"num_key_value_heads": 1,
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| 77 |
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"num_return_sequences": 1,
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| 78 |
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"output_attentions": false,
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| 79 |
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"output_hidden_states": false,
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| 80 |
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"output_scores": false,
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| 81 |
+
"pad_token_id": null,
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| 82 |
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"prefix": null,
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| 83 |
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"problem_type": null,
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| 84 |
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"pruned_heads": {},
|
| 85 |
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"qk_layer_norms_perceiver": false,
|
| 86 |
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"remove_invalid_values": false,
|
| 87 |
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"repetition_penalty": 1.0,
|
| 88 |
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"resampler_depth": 6,
|
| 89 |
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"resampler_head_dim": 96,
|
| 90 |
+
"resampler_n_heads": 16,
|
| 91 |
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"resampler_n_latents": 64,
|
| 92 |
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"return_dict": true,
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| 93 |
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"return_dict_in_generate": false,
|
| 94 |
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"sep_token_id": null,
|
| 95 |
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"suppress_tokens": null,
|
| 96 |
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"task_specific_params": null,
|
| 97 |
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"temperature": 1.0,
|
| 98 |
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"tf_legacy_loss": false,
|
| 99 |
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"tie_encoder_decoder": false,
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| 100 |
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"tie_word_embeddings": true,
|
| 101 |
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"tokenizer_class": null,
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| 102 |
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"top_k": 50,
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| 103 |
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"top_p": 1.0,
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| 104 |
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"torch_dtype": null,
|
| 105 |
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"torchscript": false,
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| 106 |
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"transformers_version": "4.46.0",
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| 107 |
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"typical_p": 1.0,
|
| 108 |
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"use_bfloat16": false
|
| 109 |
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},
|
| 110 |
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"pixel_shuffle_factor": 4,
|
| 111 |
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"pretraining_tp": 1,
|
| 112 |
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"qk_layer_norms": false,
|
| 113 |
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"rms_norm_eps": 1e-05,
|
| 114 |
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"rope_interleaved": false,
|
| 115 |
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"rope_parameters": {
|
| 116 |
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"rope_theta": 100000,
|
| 117 |
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"rope_type": "default"
|
| 118 |
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},
|
| 119 |
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"tie_word_embeddings": false,
|
| 120 |
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"transformers.js_config": {
|
| 121 |
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"kv_cache_dtype": {
|
| 122 |
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"fp16": "float16",
|
| 123 |
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"q4f16": "float16"
|
| 124 |
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}
|
| 125 |
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},
|
| 126 |
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"use_cache": true,
|
| 127 |
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"use_resampler": false,
|
| 128 |
+
"vocab_size": 49280
|
| 129 |
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},
|
| 130 |
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"tie_word_embeddings": false,
|
| 131 |
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"transformers.js_config": {
|
| 132 |
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"kv_cache_dtype": {
|
| 133 |
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"fp16": "float16",
|
| 134 |
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"q4f16": "float16"
|
| 135 |
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}
|
| 136 |
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},
|
| 137 |
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"transformers_version": "5.0.0",
|
| 138 |
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"use_cache": false,
|
| 139 |
+
"use_reentrant_checkpointing": false,
|
| 140 |
+
"vision_config": {
|
| 141 |
+
"attention_dropout": 0.0,
|
| 142 |
+
"dtype": "bfloat16",
|
| 143 |
+
"hidden_act": "gelu_pytorch_tanh",
|
| 144 |
+
"hidden_size": 768,
|
| 145 |
+
"image_size": 512,
|
| 146 |
+
"initializer_range": 0.02,
|
| 147 |
+
"intermediate_size": 3072,
|
| 148 |
+
"layer_norm_eps": 1e-06,
|
| 149 |
+
"max_image_size": {
|
| 150 |
+
"longest_edge": 512
|
| 151 |
+
},
|
| 152 |
+
"model_type": "smolvlm_vision",
|
| 153 |
+
"num_attention_heads": 12,
|
| 154 |
+
"num_channels": 3,
|
| 155 |
+
"num_hidden_layers": 12,
|
| 156 |
+
"patch_size": 16,
|
| 157 |
+
"size": {
|
| 158 |
+
"longest_edge": 2048
|
| 159 |
+
},
|
| 160 |
+
"tie_word_embeddings": false,
|
| 161 |
+
"use_base_siglip": false
|
| 162 |
+
},
|
| 163 |
+
"vocab_size": 49280
|
| 164 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"bos_token_id": 1,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
49279,
|
| 6 |
+
49279
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 2,
|
| 9 |
+
"transformers_version": "5.0.0"
|
| 10 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:066294d5273a9295d3a6edc78a49b6245082d7b7141d0f518d1b2baba5299efc
|
| 3 |
+
size 1015025832
|
processor_config.json
ADDED
|
@@ -0,0 +1,79 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"image_processor": {
|
| 3 |
+
"do_convert_rgb": true,
|
| 4 |
+
"do_image_splitting": true,
|
| 5 |
+
"do_normalize": true,
|
| 6 |
+
"do_pad": true,
|
| 7 |
+
"do_rescale": true,
|
| 8 |
+
"do_resize": true,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_processor_type": "SmolVLMImageProcessor",
|
| 15 |
+
"image_std": [
|
| 16 |
+
0.5,
|
| 17 |
+
0.5,
|
| 18 |
+
0.5
|
| 19 |
+
],
|
| 20 |
+
"max_image_size": {
|
| 21 |
+
"longest_edge": 512
|
| 22 |
+
},
|
| 23 |
+
"resample": 1,
|
| 24 |
+
"rescale_factor": 0.00392156862745098,
|
| 25 |
+
"size": {
|
| 26 |
+
"longest_edge": 2048
|
| 27 |
+
},
|
| 28 |
+
"video_sampling": {
|
| 29 |
+
"fps": 1,
|
| 30 |
+
"max_frames": 64,
|
| 31 |
+
"video_size": {
|
| 32 |
+
"longest_edge": 512
|
| 33 |
+
}
|
| 34 |
+
}
|
| 35 |
+
},
|
| 36 |
+
"image_seq_len": 64,
|
| 37 |
+
"processor_class": "SmolVLMProcessor",
|
| 38 |
+
"video_processor": {
|
| 39 |
+
"data_format": "channels_first",
|
| 40 |
+
"default_to_square": true,
|
| 41 |
+
"do_convert_rgb": true,
|
| 42 |
+
"do_image_splitting": true,
|
| 43 |
+
"do_normalize": true,
|
| 44 |
+
"do_pad": true,
|
| 45 |
+
"do_rescale": true,
|
| 46 |
+
"do_resize": true,
|
| 47 |
+
"do_sample_frames": false,
|
| 48 |
+
"fps": 1,
|
| 49 |
+
"image_mean": [
|
| 50 |
+
0.5,
|
| 51 |
+
0.5,
|
| 52 |
+
0.5
|
| 53 |
+
],
|
| 54 |
+
"image_processor_type": "SmolVLMImageProcessor",
|
| 55 |
+
"image_std": [
|
| 56 |
+
0.5,
|
| 57 |
+
0.5,
|
| 58 |
+
0.5
|
| 59 |
+
],
|
| 60 |
+
"max_image_size": {
|
| 61 |
+
"longest_edge": 512
|
| 62 |
+
},
|
| 63 |
+
"num_frames": 64,
|
| 64 |
+
"resample": 1,
|
| 65 |
+
"rescale_factor": 0.00392156862745098,
|
| 66 |
+
"return_metadata": false,
|
| 67 |
+
"size": {
|
| 68 |
+
"longest_edge": 2048
|
| 69 |
+
},
|
| 70 |
+
"video_processor_type": "SmolVLMVideoProcessor",
|
| 71 |
+
"video_sampling": {
|
| 72 |
+
"fps": 1,
|
| 73 |
+
"max_frames": 64,
|
| 74 |
+
"video_size": {
|
| 75 |
+
"longest_edge": 2048
|
| 76 |
+
}
|
| 77 |
+
}
|
| 78 |
+
}
|
| 79 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<|im_start|>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"end_of_utterance_token": "<end_of_utterance>",
|
| 7 |
+
"eos_token": "<end_of_utterance>",
|
| 8 |
+
"extra_special_tokens": [
|
| 9 |
+
"<fake_token_around_image>",
|
| 10 |
+
"<image>",
|
| 11 |
+
"<end_of_utterance>"
|
| 12 |
+
],
|
| 13 |
+
"fake_image_token": "<fake_token_around_image>",
|
| 14 |
+
"global_image_token": "<global-img>",
|
| 15 |
+
"image_token": "<image>",
|
| 16 |
+
"is_local": false,
|
| 17 |
+
"legacy": false,
|
| 18 |
+
"model_max_length": 8192,
|
| 19 |
+
"model_specific_special_tokens": {
|
| 20 |
+
"end_of_utterance_token": "<end_of_utterance>",
|
| 21 |
+
"fake_image_token": "<fake_token_around_image>",
|
| 22 |
+
"global_image_token": "<global-img>",
|
| 23 |
+
"image_token": "<image>"
|
| 24 |
+
},
|
| 25 |
+
"pad_token": "<|im_end|>",
|
| 26 |
+
"processor_class": "SmolVLMProcessor",
|
| 27 |
+
"tokenizer_class": "TokenizersBackend",
|
| 28 |
+
"truncation_side": "left",
|
| 29 |
+
"unk_token": "<|endoftext|>",
|
| 30 |
+
"vocab_size": 49152
|
| 31 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f354a237fc57bc12f7f78a490f0b9fd8c67b34c09097ad0da6dc6a9edf4cfd50
|
| 3 |
+
size 5649
|