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README.md ADDED
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+ ---
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+ license: other
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+ license_name: yi-34b
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+ license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
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+ tags:
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+ - merge
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+ - roleplay
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+ - exl2
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+ - not-for-all-audiences
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+ ---
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+
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+ # Merged-RP-Stew-V2-34B - EXL2 5.0bpw
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+
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+ This is a 5.0bpw EXL2 quant of [ParasiticRogue/Merged-RP-Stew-V2-34B](https://huggingface.co/ParasiticRogue/Merged-RP-Stew-V2-34B)
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+
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+ Details about the model and the merge info can be found at the above mode page.
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+
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+
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+ ## EXL2 Version
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+
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+ These quants were made with exllamav2 version 0.0.17. Quants made on this version of EXL2 may not working on older versions of the exllamav2 library.
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+
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+ If you have problems loading these models, please update Text Generation WebUI to the latest version.
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+
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+
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+ ## Perplexity Scoring
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+
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+ Below are the perplexity scores for the EXL2 models. A lower score is better.
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+
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+
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+ | Quant Level | Perplexity Score |
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+ |-------------|------------------|
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+ | 8.0 | 5.2805 |
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+ | 7.0 | 5.2841 |
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+ | 6.0 | 5.2789 |
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+ | 5.0 | 5.2930 |
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+ | 4.5 | 5.3110 |
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+ | 4.0 | 5.3663 |
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+ | 3.5 | 5.4860 |
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+
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+
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+ ## EQ Bench
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+
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+ Here are the EQ Bench scores for the EXL2 quants using Alpaca, ChatML and Vicuna-Chat prompt templates. A higher score is better.
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+
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+
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+ | Quant Size | Instruct Template | Score |
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+ |------------|-------------------|-------|
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+ | 8.0 | Alpaca | 75.02 |
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+ | 8.0 | ChatML | 73.82 |
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+ | 8.0 | Vicuna-Chat | 73.53 |
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+ | 7.0 | Alpaca | 74.96 |
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+ | 7.0 | ChatML | 74.22 |
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+ | 7.0 | Vicuna-Chat | 72.71 |
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+ | 6.0 | Alpaca | 75.11 |
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+ | 6.0 | ChatML | 74.29 |
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+ | 6.0 | Vicuna-Chat | 74.16 |
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+ | 5.0 | Alpaca | 74.11 |
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+ | 5.0 | ChatML | 72.74 |
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+ | 5.0 | Vicuna-Chat | 73.28 |
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+ | 4.5 | Alpaca | 73.18 |
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+ | 4.5 | ChatML | 73.62 |
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+ | 4.5 | Vicuna-Chat | 73.32 |
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+ | 4.0 | Alpaca | 71.85 |
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+ | 4.0 | ChatML | 73.99 |
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+ | 4.0 | Vicuna-Chat | 74.74 |
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+ | 3.5 | Alpaca | 73.73 |
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+ | 3.5 | ChatML | 72.07 |
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+ | 3.5 | Vicuna-Chat | 73.56 |
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+
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+ ### Vicuna Chat Template
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+
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+ This is the Vicuna-Chat template yaml that was used in EQ bench. It was tested in Text Generation Web UI and seemed to produce accurate results.
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+
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+ ```yaml
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+ user: "USER:"
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+ bot: "ASSISTANT:"
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+ turn_template: "<|user|> <|user-message|><|im_end|>\n<|bot|> <|bot-message|><|im_end|></s>\n"
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+ context: "<|system-message|><|im_end|>\n\n"
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+ system_message: "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions."
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+ ```
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+
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+ ### Perplexity Script
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+
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+ This was the script used for perplexity testing.
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+
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+ ```bash
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+ #!/bin/bash
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+
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+ # Activate the conda environment
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+ source ~/miniconda3/etc/profile.d/conda.sh
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+ conda activate exllamav2
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+
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+ # Set the model name
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+ MODEL_NAME="Merged-RP-Stew-V2-34B"
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+ BIT_PRECISIONS=(8.0 7.0 6.0 5.0 4.5 4.0 3.5 3.0 2.65 2.4)
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+
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+ for BIT_PRECISION in "${BIT_PRECISIONS[@]}"
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+ do
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+ MODEL_DIR="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw"
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+
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+ if [ -d "$MODEL_DIR" ]; then
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+ output=$(python test_inference.py -m "$MODEL_DIR" -gs 21,24 -ed data/wikitext/wikitext-2-v1.parquet)
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+ score=$(echo "$output" | grep -oP 'Evaluation perplexity: \K[\d.]+')
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+ echo "BPW: $BIT_PRECISION, Score: $score"
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+ fi
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+
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+ done
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+ ```
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+
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+
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+ ## Quant Details
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+
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+ This is the script used for quantization. These quants were calibrated against Bluemoon-Light's Chat Vicuna training data.
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+
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+ ```bash
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+ #!/bin/bash
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+
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+ # Activate the conda environment
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+ source ~/miniconda3/etc/profile.d/conda.sh
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+ conda activate exllamav2
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+
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+ # Set the model name and bit size
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+ MODEL_NAME="Merged-RP-Stew-V2-34B"
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+ BIT_PRECISION=5.0
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+
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+ # Define variables
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+ MODEL_DIR="models/$MODEL_NAME"
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+ OUTPUT_DIR="exl2_$MODEL_NAME"
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+ MEASUREMENT_FILE="measurements/$MODEL_NAME.json"
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+ CONVERTED_FOLDER="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw"
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+ CALIBRATION_DATASET="data/Bluemoon-Light/chat-vicuna.parquet"
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+
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+ # Create directories
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+ rm -r "$OUTPUT_DIR"
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+ mkdir "$OUTPUT_DIR"
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+ mkdir "$CONVERTED_FOLDER"
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+
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+ # Run conversion commands
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+ python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -om $MEASUREMENT_FILE -c $CALIBRATION_DATASET
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+ python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -m $MEASUREMENT_FILE -b $BIT_PRECISION -c $CALIBRATION_DATASET -cf $CONVERTED_FOLDER
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "Merged-RP-Stew-V2-34B",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 7168,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 20480,
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+ "max_position_embeddings": 200000,
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+ "model_type": "llama",
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+ "num_attention_heads": 56,
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+ "num_hidden_layers": 60,
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+ "num_key_value_heads": 8,
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+ "pad_token_id": 0,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 5000000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.39.1",
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+ "use_cache": true,
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+ "vocab_size": 64000,
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+ "quantization_config": {
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+ "quant_method": "exl2",
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+ "version": "0.0.17",
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+ "bits": 5.0,
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+ "head_bits": 6,
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+ "calibration": {
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+ "rows": 100,
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+ "length": 2048,
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+ "dataset": "chat-vicuna.parquet"
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+ }
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+ }
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+ }
model.safetensors.index.json ADDED
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+ "tokenizer_class": "LlamaTokenizer",
40
+ "truncation_side": "right",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false
43
+ }