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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,186 @@
+---
+library_name: transformers
+language:
+- en
+- fr
+- de
+- es
+- it
+- pt
+- ja
+- ko
+- zh
+- ar
+license: cc-by-nc-4.0
+tags:
+- exl2
+---
+
+# c4ai-command-r-plus - EXL2 7.0bpw
+
+This is a 7.0bpw EXL2 quant of [CohereForAI/c4ai-command-r-plus](https://huggingface.co/CohereForAI/c4ai-command-r-plus)
+
+Details about the model can be found at the above model page.
+
+## Turbodep EXL2 Quants
+
+This repo only has specific quants not already done at [turboderp/command-r-plus-103B-exl2](https://huggingface.co/turboderp/command-r-plus-103B-exl2)
+
+Quants marked as turboderp can be downloaded from that repo.
+
+## EXL2 Version
+
+These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not work 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 | Repo |
+|-------------|------------------|------|
+| 6.0 | 4.7068 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 5.0 | 4.7309 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 4.5 | 4.8111 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 4.25 | 4.8292 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 4.0 | 4.8603 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 3.75 | 4.9112 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 3.5 | 4.9592 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 3.25 | 5.0631 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 3.0 | 5.2050 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+| 2.5 | 5.6681 | [turboderp](https://huggingface.co/turboderp/command-r-plus-103B-exl2) |
+
+
+## EQ Bench
+
+Here are the EQ Bench scores for the EXL2 quants using Alpaca, ChatML, Command-R and Command-R-Plus prompt templates. A higher score is better.
+
+_TODO_
+
+### Command-R-Plus Template
+
+This is the Command-R-Plus template yaml that was used in EQ bench(which uses Text Generation Web UI yaml templates). It adds BOS_TOKEN into the starter prompt.
+
+_text-generation-webui/instruction-templates/Command-R-Plus.yaml_:
+```yaml
+instruction_template: |-
+  {%- if messages[0]['role'] == 'system' -%}
+      {%- set loop_messages = messages[1:] -%}
+      {%- set system_message = messages[0]['content'] -%}
+  {%- elif false == true -%}
+      {%- set loop_messages = messages -%}
+      {%- set system_message = 'You are Command-R, a brilliant, sophisticated, AI-assistant trained to assist human users by providing thorough responses. You are trained by Cohere.' -%}
+  {%- else -%}
+      {%- set loop_messages = messages -%}
+      {%- set system_message = false -%}
+  {%- endif -%}
+  {%- if system_message != false -%}
+      {{ '<BOS_TOKEN><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}
+  {%- endif -%}
+  {%- for message in loop_messages -%}
+      {%- set content = message['content'] -%}
+      {%- if message['role'] == 'user' -%}
+          {{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}
+      {%- elif message['role'] == 'assistant' -%}
+          {{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'  + content.strip() + '<|END_OF_TURN_TOKEN|>' }}
+      {%- endif -%}
+  {%- endfor -%}
+  {%- if add_generation_prompt -%}
+      {{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}
+  {%- endif -%}
+
+```
+
+### 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 and bit size
+MODEL_NAME="c4ai-command-r-plus"
+BIT_PRECISIONS=(8.0 7.5 7.0 6.5 5.5 2.75 2.25)
+
+# MODEL_NAME="turboderp_command-r-plus-103B"
+# BIT_PRECISIONS=(6.0 5.0 4.5 4.25 4.0 3.75 3.5 3.25 3.0 2.5)
+
+# Print the markdown table header
+echo "| Quant Level | Perplexity Score |"
+echo "|-------------|------------------|"
+
+for BIT_PRECISION in "${BIT_PRECISIONS[@]}"
+do
+  MODEL_DIR="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw"
+#   MODEL_DIR="models/${MODEL_NAME}-exl2_${BIT_PRECISION}bpw"
+  if [ -d "$MODEL_DIR" ]; then
+    output=$(python test_inference.py -m "$MODEL_DIR" -gs 22,24 -ed data/wikitext/wikitext-2-v1.parquet)
+    score=$(echo "$output" | grep -oP 'Evaluation perplexity: \K[\d.]+')
+    echo "| $BIT_PRECISION | $score |"
+  fi
+done
+```
+
+
+## Quant Details
+
+This is the script used for quantization.
+
+```bash
+#!/bin/bash
+
+# Activate the conda environment
+source ~/miniconda3/etc/profile.d/conda.sh
+conda activate exllamav2
+
+# Set the model name and bit size
+MODEL_NAME="c4ai-command-r-plus"
+
+# Define variables
+MODEL_DIR="models/$MODEL_NAME"
+OUTPUT_DIR="exl2_$MODEL_NAME"
+MEASUREMENT_FILE="measurements/$MODEL_NAME.json"
+
+# Create the measurement file if needed
+if [ ! -f "$MEASUREMENT_FILE" ]; then
+    echo "Creating $MEASUREMENT_FILE"
+    # Create directories
+    if [ -d "$OUTPUT_DIR" ]; then
+        rm -r "$OUTPUT_DIR"
+    fi
+    mkdir "$OUTPUT_DIR"
+
+    python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -om $MEASUREMENT_FILE
+fi
+
+# Choose one of the below. Either create a single quant for testing or a batch of them.
+# BIT_PRECISIONS=(5.0)
+BIT_PRECISIONS=(8.0 7.5 6.5 5.5 2.75 2.25)
+
+for BIT_PRECISION in "${BIT_PRECISIONS[@]}"
+do
+    CONVERTED_FOLDER="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw"
+
+    # If it doesn't already exist, make the quant
+    if [ ! -d "$CONVERTED_FOLDER" ]; then
+
+        echo "Creating $CONVERTED_FOLDER"
+
+        # Create directories
+        if [ -d "$OUTPUT_DIR" ]; then
+            rm -r "$OUTPUT_DIR"
+        fi
+        mkdir "$OUTPUT_DIR"
+        mkdir "$CONVERTED_FOLDER"
+        
+        # Run conversion commands  
+        python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -m $MEASUREMENT_FILE -b $BIT_PRECISION -cf $CONVERTED_FOLDER
+
+    fi
+done
+```

config.json

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+{
+    "architectures": [
+        "CohereForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 5,
+    "eos_token_id": 255001,
+    "hidden_act": "silu",
+    "hidden_size": 12288,
+    "initializer_range": 0.02,
+    "intermediate_size": 33792,
+    "layer_norm_eps": 1e-05,
+    "logit_scale": 0.8333333333333334,
+    "max_position_embeddings": 8192,
+    "model_max_length": 131072,
+    "model_type": "cohere",
+    "num_attention_heads": 96,
+    "num_hidden_layers": 64,
+    "num_key_value_heads": 8,
+    "pad_token_id": 0,
+    "rope_theta": 75000000.0,
+    "torch_dtype": "float16",
+    "transformers_version": "4.40.0.dev0",
+    "use_cache": true,
+    "use_qk_norm": true,
+    "vocab_size": 256000,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.18",
+        "bits": 7.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 5,
+  "eos_token_id": 255001,
+  "pad_token_id": 0,
+  "transformers_version": "4.40.0.dev0"
+}

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