Uploading AWQ model
Browse files- README.md +69 -0
- added_tokens.json +4 -0
- config.json +36 -0
- generation_config.json +7 -0
- model.safetensors +3 -0
- special_tokens_map.json +36 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +67 -0
README.md
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---
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license: apache-2.0
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---
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---
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base_model: senseable/WestLake-7B-v2
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license: apache-2.0
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datasets:
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- cognitivecomputations/samantha-data
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library_name: transformers
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model_creator: cognitivecomputations
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model_name: Samantha 1.1 WestLake 7B - AWQ
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model_type: mistral
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pipeline_tag: text-generation
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prompt_template: '<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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'
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quantized_by: Suparious
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---
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# Samantha 7B v1.1 laser - AWQ
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- Model creator: [cognitivecomputations](https://huggingface.co/cognitivecomputations)
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- Original model: [WestLake 7B v2](https://huggingface.co/cognitivecomputations/WestLake-7B-v2)
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- Fine Tuning: [cognitivecomputations](https://huggingface.co/cognitivecomputations/samantha-1.1-westlake-7b-laser)
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It follows the implementation of [laserRMT](https://github.com/cognitivecomputations/laserRMT)
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/DQ2iBVPM1PA4GKQBgvMEO.png)
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## Model description
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This repo contains AWQ model files for [cognitivecomputations's Samantha 7B v1.1](https://huggingface.co/cognitivecomputations/samantha-1.1-westlake-7b-laser).
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These files were quantised using hardware kindly provided by [SolidRusT Networks](https://solidrust.net/).
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### About AWQ
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AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.
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AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.
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It is supported by:
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- [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ
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- [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types.
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- [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference)
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- [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers
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- [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code
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## Prompt template: ChatML
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```plaintext
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<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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Also working with Basic Mistral format:
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```plaintext
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<|system|>
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</s>
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<|user|>
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{prompt}</s>
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<|assistant|>
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```
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added_tokens.json
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{
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"<|im_end|>": 32000,
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"<|im_start|>": 32001
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}
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config.json
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{
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"_name_or_path": "./models/samantha-1.1-westlake-7b-laser",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 32000,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pad_token_id": 2,
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"quantization_config": {
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"bits": 4,
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"group_size": 128,
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"modules_to_not_convert": null,
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"quant_method": "awq",
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"version": "gemm",
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"zero_point": true
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},
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.37.2",
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"unsloth_version": "2024.1",
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"use_cache": false,
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"vocab_size": 32002
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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": 1,
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"do_sample": true,
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"eos_token_id": 2,
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"transformers_version": "4.37.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ac1d541788a07f6bc941ab70ddb369d9a88fb0d3e27e730caff7bbc83e8429c4
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size 4150913000
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<unk>",
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"<s>",
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"</s>",
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"<|im_end|>"
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],
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"bos_token": {
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"content": "<s>",
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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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"eos_token": {
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"content": "<|im_end|>",
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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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"pad_token": {
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"content": "<unk>",
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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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"unk_token": {
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"content": "<unk>",
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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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}
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tokenizer.json
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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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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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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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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"special": true
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},
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"1": {
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"content": "<s>",
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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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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"32000": {
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"content": "<|im_end|>",
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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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"special": true
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},
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"32001": {
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"content": "<|im_start|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": false
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}
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},
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"additional_special_tokens": [
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"<unk>",
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"<s>",
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"</s>",
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"<|im_end|>"
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],
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"bos_token": "<s>",
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"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|im_end|>",
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"legacy": true,
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"model_max_length": 255,
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"pad_token": "<unk>",
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"padding_side": "right",
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "LlamaTokenizer",
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"trust_remote_code": false,
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"unk_token": "<unk>",
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"use_default_system_prompt": true,
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"use_fast": true
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}
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