MLX
Safetensors
English
falcon_mamba
Eval Results
8-bit precision
ybelkada commited on
Commit
5136045
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README.md ADDED
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+ ---
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+ base_model: tiiuae/falcon-mamba-7b
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+ datasets:
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+ - tiiuae/falcon-refinedweb
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+ - HuggingFaceFW/fineweb-edu
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+ language:
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+ - en
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+ license: other
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+ license_name: falcon-mamba-7b-license
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+ license_link: https://falconllm.tii.ae/falcon-mamba-7b-terms-and-conditions.html
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+ tags:
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+ - mlx
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+ model-index:
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+ - name: falcon-mamba-7b
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: IFEval (0-Shot)
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+ type: HuggingFaceH4/ifeval
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: inst_level_strict_acc and prompt_level_strict_acc
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+ value: 33.36
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+ name: strict accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=tiiuae/falcon-mamba-7b
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: BBH (3-Shot)
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+ type: BBH
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+ args:
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+ num_few_shot: 3
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+ metrics:
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+ - type: acc_norm
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+ value: 19.88
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=tiiuae/falcon-mamba-7b
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MATH Lvl 5 (4-Shot)
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+ type: hendrycks/competition_math
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+ args:
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+ num_few_shot: 4
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+ metrics:
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+ - type: exact_match
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+ value: 3.63
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+ name: exact match
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=tiiuae/falcon-mamba-7b
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: GPQA (0-shot)
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+ type: Idavidrein/gpqa
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 8.05
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=tiiuae/falcon-mamba-7b
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MuSR (0-shot)
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+ type: TAUR-Lab/MuSR
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 10.86
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=tiiuae/falcon-mamba-7b
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MMLU-PRO (5-shot)
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+ type: TIGER-Lab/MMLU-Pro
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+ config: main
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 14.47
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=tiiuae/falcon-mamba-7b
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+ name: Open LLM Leaderboard
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+ ---
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+
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+ # mlx-community/falcon-mamba-7b-8bit
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+
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+ The Model [mlx-community/falcon-mamba-7b-8bit](https://huggingface.co/mlx-community/falcon-mamba-7b-8bit) was converted to MLX format from [tiiuae/falcon-mamba-7b](https://huggingface.co/tiiuae/falcon-mamba-7b) using mlx-lm version **0.19.2**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("mlx-community/falcon-mamba-7b-8bit")
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+
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+ prompt="hello"
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+
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+ if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
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+ messages = [{"role": "user", "content": prompt}]
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+ prompt = tokenizer.apply_chat_template(
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+ messages, tokenize=False, add_generation_prompt=True
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+ )
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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```
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+ {
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+ "architectures": [
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+ "FalconMambaForCausalLM"
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+ ],
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+ "bos_token_id": 0,
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+ "conv_kernel": 4,
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+ "eos_token_id": 11,
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+ "expand": 16,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.1,
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+ "intermediate_size": 8192,
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+ "layer_norm_epsilon": 1e-05,
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+ "model_type": "falcon_mamba",
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+ "num_hidden_layers": 64,
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+ "pad_token_id": 11,
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+ "quantization": {
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+ "group_size": 64,
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+ "bits": 8
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+ },
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+ "quantization_config": {
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+ "group_size": 64,
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+ "bits": 8
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+ },
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+ "rescale_prenorm_residual": false,
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+ "residual_in_fp32": true,
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+ "state_size": 16,
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+ "tie_word_embeddings": false,
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+ "time_step_floor": 0.0001,
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+ "time_step_init_scheme": "random",
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+ "time_step_max": 0.1,
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+ "time_step_min": 0.001,
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+ "time_step_rank": 256,
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+ "time_step_scale": 1.0,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.43.0.dev0",
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+ "use_bias": false,
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+ "use_cache": true,
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+ "use_conv_bias": true,
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+ "vocab_size": 65024
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+ }
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+ "lstrip": false,
18
+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ }
22
+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
@@ -0,0 +1,123 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "0": {
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+ "content": ">>TITLE<<",
6
+ "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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+ "1": {
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+ "content": ">>ABSTRACT<<",
14
+ "lstrip": false,
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+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
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+ },
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+ "2": {
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+ "content": ">>INTRODUCTION<<",
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+ "lstrip": false,
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+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
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+ },
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+ "3": {
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+ "content": ">>SUMMARY<<",
30
+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
33
+ "single_word": false,
34
+ "special": true
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+ },
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+ "4": {
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+ "content": ">>COMMENT<<",
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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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+ "5": {
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+ "content": ">>ANSWER<<",
46
+ "lstrip": false,
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+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false,
50
+ "special": true
51
+ },
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+ "6": {
53
+ "content": ">>QUESTION<<",
54
+ "lstrip": false,
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+ "normalized": false,
56
+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "7": {
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+ "content": ">>DOMAIN<<",
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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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+ "8": {
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+ "content": ">>PREFIX<<",
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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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+ "9": {
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+ "content": ">>SUFFIX<<",
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+ "lstrip": false,
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+ "normalized": false,
80
+ "rstrip": false,
81
+ "single_word": false,
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+ "special": true
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+ },
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+ "10": {
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+ "content": ">>MIDDLE<<",
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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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+ "11": {
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+ "content": "<|endoftext|>",
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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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+ }
100
+ },
101
+ "additional_special_tokens": [
102
+ ">>TITLE<<",
103
+ ">>ABSTRACT<<",
104
+ ">>INTRODUCTION<<",
105
+ ">>SUMMARY<<",
106
+ ">>COMMENT<<",
107
+ ">>ANSWER<<",
108
+ ">>QUESTION<<",
109
+ ">>DOMAIN<<",
110
+ ">>PREFIX<<",
111
+ ">>SUFFIX<<",
112
+ ">>MIDDLE<<"
113
+ ],
114
+ "clean_up_tokenization_spaces": true,
115
+ "eos_token": "<|endoftext|>",
116
+ "model_input_names": [
117
+ "input_ids",
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+ "attention_mask"
119
+ ],
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+ "model_max_length": 1000000000000000019884624838656,
121
+ "padding_side": "left",
122
+ "tokenizer_class": "PreTrainedTokenizerFast"
123
+ }