Instructions to use ProfEngel/OwlLM2-e2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use ProfEngel/OwlLM2-e2b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ProfEngel/OwlLM2-e2b", filename="OwlLM2-e2b.Q8_0.gguf", )
llm.create_chat_completion( messages = "\"The answer to the universe is 42\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ProfEngel/OwlLM2-e2b with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ProfEngel/OwlLM2-e2b:Q8_0 # Run inference directly in the terminal: llama-cli -hf ProfEngel/OwlLM2-e2b:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ProfEngel/OwlLM2-e2b:Q8_0 # Run inference directly in the terminal: llama-cli -hf ProfEngel/OwlLM2-e2b:Q8_0
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf ProfEngel/OwlLM2-e2b:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf ProfEngel/OwlLM2-e2b:Q8_0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf ProfEngel/OwlLM2-e2b:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ProfEngel/OwlLM2-e2b:Q8_0
Use Docker
docker model run hf.co/ProfEngel/OwlLM2-e2b:Q8_0
- LM Studio
- Jan
- Ollama
How to use ProfEngel/OwlLM2-e2b with Ollama:
ollama run hf.co/ProfEngel/OwlLM2-e2b:Q8_0
- Unsloth Studio
How to use ProfEngel/OwlLM2-e2b with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ProfEngel/OwlLM2-e2b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ProfEngel/OwlLM2-e2b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ProfEngel/OwlLM2-e2b to start chatting
- Docker Model Runner
How to use ProfEngel/OwlLM2-e2b with Docker Model Runner:
docker model run hf.co/ProfEngel/OwlLM2-e2b:Q8_0
- Lemonade
How to use ProfEngel/OwlLM2-e2b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ProfEngel/OwlLM2-e2b:Q8_0
Run and chat with the model
lemonade run user.OwlLM2-e2b-Q8_0
List all available models
lemonade list
(Trained with Unsloth)
Browse files- config.json +209 -0
- generation_config.json +13 -0
config.json
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| 1 |
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{
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"architectures": [
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"Gemma3nForConditionalGeneration"
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],
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"audio_config": {
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"conf_attention_chunk_size": 12,
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"conf_attention_logit_cap": 50.0,
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"conf_conv_kernel_size": 5,
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"conf_num_attention_heads": 8,
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"conf_num_hidden_layers": 12,
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"conf_reduction_factor": 4,
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"input_feat_size": 128,
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"rms_norm_eps": 1e-06,
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"sscp_conv_channel_size": [
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],
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"sscp_conv_group_norm_eps": 0.001,
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"sscp_conv_kernel_size": [
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[
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[
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"sscp_conv_stride_size": [
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[
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[
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],
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"torch_dtype": "bfloat16",
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"vocab_offset": 262272,
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"vocab_size": 128
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},
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| 49 |
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"audio_soft_tokens_per_image": 188,
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| 50 |
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"audio_token_id": 262273,
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| 51 |
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"boa_token_id": 256000,
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| 52 |
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"boi_token_id": 255999,
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| 53 |
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"bos_token_id": 2,
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| 54 |
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"eoa_token_id": 262272,
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| 55 |
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"eoi_token_id": 262144,
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| 56 |
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"eos_token_id": 106,
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| 57 |
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"image_token_id": 262145,
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| 58 |
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"initializer_range": 0.02,
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| 59 |
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"model_type": "gemma3n",
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| 60 |
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"pad_token_id": 0,
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| 61 |
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"text_config": {
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"activation_sparsity_pattern": [
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"altup_active_idx": 0,
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"altup_coef_clip": 120.0,
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| 96 |
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"altup_correct_scale": true,
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| 97 |
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"altup_num_inputs": 4,
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| 98 |
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"attention_bias": false,
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| 99 |
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"attention_dropout": 0.0,
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| 100 |
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"final_logit_softcapping": 30.0,
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| 101 |
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"head_dim": 256,
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| 102 |
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"hidden_activation": "gelu_pytorch_tanh",
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| 103 |
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"hidden_size": 2048,
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| 104 |
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"hidden_size_per_layer_input": 256,
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| 105 |
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"intermediate_size": [
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"laurel_rank": 64,
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| 139 |
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"layer_types": [
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention"
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| 171 |
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"max_position_embeddings": 32768,
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| 172 |
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"model_type": "gemma3n_text",
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| 173 |
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"num_attention_heads": 8,
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| 174 |
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"num_hidden_layers": 30,
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| 175 |
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"num_key_value_heads": 2,
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| 176 |
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"num_kv_shared_layers": 10,
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| 177 |
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"rms_norm_eps": 1e-06,
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| 178 |
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"rope_local_base_freq": 10000.0,
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| 179 |
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"rope_scaling": null,
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| 180 |
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"rope_theta": 1000000.0,
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| 181 |
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"sliding_window": 512,
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| 182 |
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"torch_dtype": "bfloat16",
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| 183 |
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"use_cache": true,
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| 184 |
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"vocab_size": 262400,
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| 185 |
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"vocab_size_per_layer_input": 262144
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| 186 |
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},
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| 187 |
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"torch_dtype": "bfloat16",
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| 188 |
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"transformers_version": "4.53.2",
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| 189 |
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"unsloth_fixed": true,
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| 190 |
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"unsloth_version": "2025.7.6",
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| 191 |
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"vision_config": {
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| 192 |
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"architecture": "mobilenetv5_300m_enc",
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| 193 |
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"do_pooling": false,
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| 194 |
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"hidden_size": 2048,
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| 195 |
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"initializer_range": 0.02,
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| 196 |
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"label_names": [
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| 197 |
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"LABEL_0",
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| 198 |
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"LABEL_1"
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| 199 |
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],
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| 200 |
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"model_args": null,
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| 201 |
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"model_type": "gemma3n_vision",
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| 202 |
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"num_classes": 2,
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| 203 |
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"rms_norm_eps": 1e-06,
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| 204 |
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"torch_dtype": "bfloat16",
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| 205 |
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"vocab_offset": 262144,
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| 206 |
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"vocab_size": 128
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| 207 |
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},
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| 208 |
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"vision_soft_tokens_per_image": 256
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| 209 |
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}
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generation_config.json
ADDED
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{
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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| 4 |
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"do_sample": true,
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"eos_token_id": [
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1,
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106
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],
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| 9 |
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"pad_token_id": 0,
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| 10 |
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"top_k": 64,
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| 11 |
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"top_p": 0.95,
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| 12 |
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"transformers_version": "4.53.2"
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| 13 |
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}
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