Text Generation
Transformers
Safetensors
qwen2
mergekit
Merge
conversational
text-generation-inference
Instructions to use ForSureTesterSim/merge-test-2-sibling-violation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ForSureTesterSim/merge-test-2-sibling-violation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ForSureTesterSim/merge-test-2-sibling-violation") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ForSureTesterSim/merge-test-2-sibling-violation") model = AutoModelForCausalLM.from_pretrained("ForSureTesterSim/merge-test-2-sibling-violation") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ForSureTesterSim/merge-test-2-sibling-violation with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ForSureTesterSim/merge-test-2-sibling-violation" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ForSureTesterSim/merge-test-2-sibling-violation", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ForSureTesterSim/merge-test-2-sibling-violation
- SGLang
How to use ForSureTesterSim/merge-test-2-sibling-violation 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 "ForSureTesterSim/merge-test-2-sibling-violation" \ --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": "ForSureTesterSim/merge-test-2-sibling-violation", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "ForSureTesterSim/merge-test-2-sibling-violation" \ --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": "ForSureTesterSim/merge-test-2-sibling-violation", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ForSureTesterSim/merge-test-2-sibling-violation with Docker Model Runner:
docker model run hf.co/ForSureTesterSim/merge-test-2-sibling-violation
Automated upload of Merge Test 2 (Sibling Violation) via DELLA-Merging
Browse files- README.md +54 -0
- config.json +62 -0
- generation_config.json +9 -0
- mergekit_config.yml +19 -0
- model.safetensors +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +35 -0
README.md
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---
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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- nvidia/Nemotron-Research-Reasoning-Qwen-1.5B
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- nvidia/OpenMath-Nemotron-1.5B
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- Fate-Zero/Archer2.0-Code-1.5B-Preview
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# merge_test_2
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [DELLA](https://arxiv.org/abs/2406.11617) merge method using [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) as a base.
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### Models Merged
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The following models were included in the merge:
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* [nvidia/Nemotron-Research-Reasoning-Qwen-1.5B](https://huggingface.co/nvidia/Nemotron-Research-Reasoning-Qwen-1.5B)
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* [nvidia/OpenMath-Nemotron-1.5B](https://huggingface.co/nvidia/OpenMath-Nemotron-1.5B)
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* [Fate-Zero/Archer2.0-Code-1.5B-Preview](https://huggingface.co/Fate-Zero/Archer2.0-Code-1.5B-Preview)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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merge_method: della
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base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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dtype: bfloat16
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models:
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- model: nvidia/OpenMath-Nemotron-1.5B
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parameters:
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weight: 1.0
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density: 0.6
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epsilon: 0.3
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- model: nvidia/Nemotron-Research-Reasoning-Qwen-1.5B
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parameters:
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weight: 1.0
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density: 0.6
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epsilon: 0.3
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- model: Fate-Zero/Archer2.0-Code-1.5B-Preview
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parameters:
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weight: 1.0
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density: 0.6
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epsilon: 0.3
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```
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "bfloat16",
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"intermediate_size": 8960,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 131072,
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"max_window_layers": 21,
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"model_type": "qwen2",
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"num_attention_heads": 12,
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"num_hidden_layers": 28,
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"num_key_value_heads": 2,
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"pad_token_id": null,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 10000,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": false,
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"transformers_version": "5.10.2",
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"use_cache": true,
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"use_mrope": false,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 151646,
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"eos_token_id": 151643,
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"do_sample": true,
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"temperature": 0.6,
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"top_p": 0.95,
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"transformers_version": "4.39.3"
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}
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mergekit_config.yml
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merge_method: della
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base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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dtype: bfloat16
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models:
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- model: nvidia/OpenMath-Nemotron-1.5B
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parameters:
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weight: 1.0
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density: 0.6
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epsilon: 0.3
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- model: nvidia/Nemotron-Research-Reasoning-Qwen-1.5B
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parameters:
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weight: 1.0
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density: 0.6
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epsilon: 0.3
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- model: Fate-Zero/Archer2.0-Code-1.5B-Preview
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parameters:
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weight: 1.0
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density: 0.6
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epsilon: 0.3
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6c9fb9a3ab2bfd1a0c9937ff93607b0093655f40951eb899cff9270b161bad22
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size 3554214752
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tokenizer.json
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See raw diff
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"bos_token": {
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| 5 |
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"__type": "AddedToken",
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"content": "<|begin▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"legacy": true,
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"model_max_length": 16384,
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| 23 |
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"pad_token": {
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"__type": "AddedToken",
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| 25 |
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"content": "<|end▁of▁sentence|>",
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"lstrip": false,
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| 27 |
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"sp_model_kwargs": {},
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"unk_token": null,
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"tokenizer_class": "LlamaTokenizerFast",
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"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<|User|>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<|Assistant|><|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>' + message['content'] + '<|end▁of▁sentence|>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<|Assistant|>' + content + '<|end▁of▁sentence|>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<|tool▁outputs▁begin|><|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<|Assistant|><think>\\n'}}{% endif %}"
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}
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