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README.md

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+---
+license: other
+license_name: yi-34b
+license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
+tags:
+- merge
+- roleplay
+- exl2
+- not-for-all-audiences
+---
+
+# Merged-RP-Stew-V2-34B - EXL2 4.0bpw
+
+This is a 4.0bpw EXL2 quant of [ParasiticRogue/Merged-RP-Stew-V2-34B](https://huggingface.co/ParasiticRogue/Merged-RP-Stew-V2-34B)
+
+Details about the model and the merge info can be found at the above mode page.
+
+
+## EXL2 Version
+
+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.
+
+If you have problems loading these models, please update Text Generation WebUI to the latest version.
+
+
+## Perplexity Scoring
+
+Below are the perplexity scores for the EXL2 models. A lower score is better. 
+ 
+
+| Quant Level | Perplexity Score |
+|-------------|------------------|
+| 8.0         | 5.2805           |
+| 7.0         | 5.2841           |
+| 6.0         | 5.2789           |
+| 5.0         | 5.2930           |
+| 4.5         | 5.3110           |
+| 4.0         | 5.3663           |
+| 3.5         | 5.4860           |
+
+
+## EQ Bench
+
+Here are the EQ Bench scores for the EXL2 quants using Alpaca, ChatML and Vicuna-Chat prompt templates. A higher score is better.
+
+
+| Quant Size | Instruct Template | Score |
+|------------|-------------------|-------|
+| 8.0        | Alpaca            | 75.02 |
+| 8.0        | ChatML            | 73.82 |
+| 8.0        | Vicuna-Chat       | 73.53 |
+| 7.0        | Alpaca            | 74.96 |
+| 7.0        | ChatML            | 74.22 |
+| 7.0        | Vicuna-Chat       | 72.71 |
+| 6.0        | Alpaca            | 75.11 |
+| 6.0        | ChatML            | 74.29 |
+| 6.0        | Vicuna-Chat       | 74.16 |
+| 5.0        | Alpaca            | 74.11 |
+| 5.0        | ChatML            | 72.74 |
+| 5.0        | Vicuna-Chat       | 73.28 |
+| 4.5        | Alpaca            | 73.18 |
+| 4.5        | ChatML            | 73.62 |
+| 4.5        | Vicuna-Chat       | 73.32 |
+| 4.0        | Alpaca            | 71.85 |
+| 4.0        | ChatML            | 73.99 |
+| 4.0        | Vicuna-Chat       | 74.74 |
+| 3.5        | Alpaca            | 73.73 |
+| 3.5        | ChatML            | 72.07 |
+| 3.5        | Vicuna-Chat       | 73.56 |
+
+### Vicuna Chat Template
+
+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.
+
+```yaml
+user: "USER:"
+bot: "ASSISTANT:"
+turn_template: "<|user|> <|user-message|><|im_end|>\n<|bot|> <|bot-message|><|im_end|></s>\n"
+context: "<|system-message|><|im_end|>\n\n"
+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."
+```
+
+### Perplexity Script
+
+This was the script used for perplexity testing.
+
+```bash
+#!/bin/bash
+
+# Activate the conda environment
+source ~/miniconda3/etc/profile.d/conda.sh
+conda activate exllamav2
+
+# Set the model name
+MODEL_NAME="Merged-RP-Stew-V2-34B"
+BIT_PRECISIONS=(8.0 7.0 6.0 5.0 4.5 4.0 3.5 3.0 2.65 2.4)
+
+for BIT_PRECISION in "${BIT_PRECISIONS[@]}"
+do
+    MODEL_DIR="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw"
+
+    if [ -d "$MODEL_DIR" ]; then
+        output=$(python test_inference.py -m "$MODEL_DIR" -gs 21,24 -ed data/wikitext/wikitext-2-v1.parquet)
+        score=$(echo "$output" | grep -oP 'Evaluation perplexity: \K[\d.]+')
+        echo "BPW: $BIT_PRECISION, Score: $score"
+    fi
+
+done
+```
+
+
+## Quant Details
+
+This is the script used for quantization. These quants were calibrated against Bluemoon-Light's Chat Vicuna training data.
+
+```bash
+#!/bin/bash
+
+# Activate the conda environment
+source ~/miniconda3/etc/profile.d/conda.sh
+conda activate exllamav2
+
+# Set the model name and bit size
+MODEL_NAME="Merged-RP-Stew-V2-34B"
+BIT_PRECISION=4.0
+
+# Define variables
+MODEL_DIR="models/$MODEL_NAME"
+OUTPUT_DIR="exl2_$MODEL_NAME"
+MEASUREMENT_FILE="measurements/$MODEL_NAME.json"
+CONVERTED_FOLDER="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw"
+CALIBRATION_DATASET="data/Bluemoon-Light/chat-vicuna.parquet"
+
+# Create directories
+rm -r "$OUTPUT_DIR"
+mkdir "$OUTPUT_DIR"
+mkdir "$CONVERTED_FOLDER"
+  
+# Run conversion commands  
+python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -om $MEASUREMENT_FILE -c $CALIBRATION_DATASET
+python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -m $MEASUREMENT_FILE -b $BIT_PRECISION -c $CALIBRATION_DATASET -cf $CONVERTED_FOLDER
+```

config.json

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+{
+    "_name_or_path": "Merged-RP-Stew-V2-34B",
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 1,
+    "eos_token_id": 2,
+    "hidden_act": "silu",
+    "hidden_size": 7168,
+    "initializer_range": 0.02,
+    "intermediate_size": 20480,
+    "max_position_embeddings": 200000,
+    "model_type": "llama",
+    "num_attention_heads": 56,
+    "num_hidden_layers": 60,
+    "num_key_value_heads": 8,
+    "pad_token_id": 0,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 5000000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.39.1",
+    "use_cache": true,
+    "vocab_size": 64000,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.17",
+        "bits": 4.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "chat-vicuna.parquet"
+        }
+    }
+}

model.safetensors.index.json

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