Quant for 3.5

README.md

@@ -10,63 +10,69 @@ language:
 tags:
 - code
 - mathematics
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
 
-## Exllama v2 Quantizations of Code-Mistral-7B
+**Code-Mistral-7B**
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.16">turboderp's ExLlamaV2 v0.0.16</a> for quantization.
 
-<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
+This Model is trained on refined version of my dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT).
+Besides this it is trained on following datasets:
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
+[Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback)
 
-Original model: https://huggingface.co/ajibawa-2023/Code-Mistral-7B
+[orca-math-word-problems-200k](https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k)
 
-| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
-| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
-| [8_0](https://huggingface.co/bartowski/Code-Mistral-7B-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
-| [6_5](https://huggingface.co/bartowski/Code-Mistral-7B-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
-| [5_0](https://huggingface.co/bartowski/Code-Mistral-7B-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB |  9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
-| [4_25](https://huggingface.co/bartowski/Code-Mistral-7B-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
-| [3_5](https://huggingface.co/bartowski/Code-Mistral-7B-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
+[Openhermes](https://huggingface.co/datasets/teknium/openhermes)
 
-## Download instructions
+The idea was to check how this Model will perform with both Code & Maths datasets. This model is very good with Coding. 
+Maths is still hit & miss but you can test out this model.
 
-With git:
+This Model is trained on massive datasets so the results are very good.
+I have used ChatML prompt format.
 
-```shell
-git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Code-Mistral-7B-exl2 Code-Mistral-7B-exl2-6_5
-```
+Kindly note this is qLoRA version, a rare exception.
 
-With huggingface hub (credit to TheBloke for instructions):
 
-```shell
-pip3 install huggingface-hub
-```
+**Training:**
+Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took almost 33 Hours. Axolotl codebase was used for training purpose.
+Entire data is trained on Mistral.
 
-To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Code-Mistral-7B-exl2`:
+**Example Prompt:**
+This model uses **ChatML** prompt format.
 
-```shell
-mkdir Code-Mistral-7B-exl2
-huggingface-cli download bartowski/Code-Mistral-7B-exl2 --local-dir Code-Mistral-7B-exl2 --local-dir-use-symlinks False
 ```
+<|im_start|>system
+You are a helpful AI assistant.<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
 
-To download from a different branch, add the `--revision` parameter:
+```
+You can modify above Prompt as per your requirement. 
 
-Linux:
 
-```shell
-mkdir Code-Mistral-7B-exl2-6_5
-huggingface-cli download bartowski/Code-Mistral-7B-exl2 --revision 6_5 --local-dir Code-Mistral-7B-exl2-6_5 --local-dir-use-symlinks False
-```
+I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
 
-Windows (which apparently doesn't like _ in folders sometimes?):
+Thank you for your love & support.
+
+
+**Example Output**
+
+
+**C++**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/jcmEZSRX7s7-B_ZybWwwN.jpeg)
+
+**Error Resolving**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/iy89IxjiZXAY4Id-ieLg7.jpeg)
+
+**Matrices**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/zFfq9lBA63wQzy0tP3_hd.jpeg)
+
+**Machine Learning**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/Nv8dCpNxRtJGkOuulKzmn.jpeg)
 
-```shell
-mkdir Code-Mistral-7B-exl2-6.5
-huggingface-cli download bartowski/Code-Mistral-7B-exl2 --revision 6_5 --local-dir Code-Mistral-7B-exl2-6.5 --local-dir-use-symlinks False
-```
 
-Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski

config.json

@@ -0,0 +1,37 @@
+{
+    "_name_or_path": "/home/mla100wus3/Downloads/Code-7B",
+    "architectures": [
+        "MistralForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 1,
+    "eos_token_id": 2,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 14336,
+    "max_position_embeddings": 32768,
+    "model_type": "mistral",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-05,
+    "rope_theta": 10000.0,
+    "sliding_window": 4096,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.38.2",
+    "use_cache": false,
+    "vocab_size": 32000,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.16",
+        "bits": 3.5,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.38.2"
+}

original_repo_url.txt

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+https://huggingface.co/ajibawa-2023/Code-Mistral-7B

output.safetensors

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+size 3419509248

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special_tokens_map.json

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+{
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+    "rstrip": false,
+    "single_word": false
+  },
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+    "normalized": false,
+    "rstrip": false,
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": true,
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+      "rstrip": false,
+      "single_word": false,
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
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+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful assistant.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'<|im_start|>system\n' + system_message + '<|im_end|>\n'}}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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+  "padding_side": "right",
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+  "tokenizer_class": "LlamaTokenizer",
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+}