Quant for 8.0
Browse files- README.md +3 -37
- all_results.json +13 -0
- config.json +26 -0
- eval_results.json +8 -0
- generation_config.json +6 -0
- model.safetensors.index.json +298 -0
- original_repo_url.txt +1 -0
- output.safetensors +3 -0
- special_tokens_map.json +28 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +46 -0
- train_results.json +8 -0
- trainer_state.json +44 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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library_name: peft
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base_model: rishiraj/CatPPT-base
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datasets:
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- HuggingFaceH4/no_robots
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language:
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- en
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widget:
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- text: |
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<|system|>
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You are a friendly chatbot who always responds in the style of a pirate</s>
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<|user|>
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How many helicopters can a human eat in one sitting?</s>
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<|assistant|>
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output:
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text: >-
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Aye, me hearties! 'Tis not likely a human can eat a helicopter in any sittin', let alone one! They be too big and made of metal, and not fit for consumption. But if ye be referrin' to helicopter snacks, like nuts and trail mix, then a human might be able to munch a goodly amount in one sittin'. Arr!
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tags:
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- generated_from_trainer
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pipeline_tag: text-generation
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model-index:
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- name: CatPPT
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results: []
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quantized_by: bartowski
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---
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-
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Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.11">turboderp's ExLlamaV2 v0.0.11</a> for quantization.
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Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
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Conversion was done using the default calibration dataset.
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Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
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Original model: https://huggingface.co/rishiraj/CatPPT
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## Download instructions
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With git:
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```shell
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git clone --single-branch --branch
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```
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With huggingface hub (credit to TheBloke for instructions):
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pip3 install huggingface-hub
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```
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To download the `main` (only useful if you only care about measurement.json) branch to a folder called `CatPPT-exl2`:
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```shell
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mkdir CatPPT-exl2
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huggingface-cli download bartowski/CatPPT-exl2 --local-dir CatPPT-exl2 --local-dir-use-symlinks False
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```
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To download from a different branch, add the `--revision` parameter:
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```shell
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mkdir CatPPT-exl2
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huggingface-cli download bartowski/CatPPT-exl2 --revision
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```
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quantized_by: bartowski
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---
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# Exllama v2 Quantizations of CatPPT at 8.0 bits per weight
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Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.11">turboderp's ExLlamaV2 v0.0.11</a> for quantization.
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Conversion was done using the default calibration dataset.
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Original model: https://huggingface.co/rishiraj/CatPPT
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## Download instructions
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With git:
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```shell
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git clone --single-branch --branch 8.0 https://huggingface.co/bartowski/CatPPT-exl2
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```
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With huggingface hub (credit to TheBloke for instructions):
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pip3 install huggingface-hub
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```
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To download from a different branch, add the `--revision` parameter:
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```shell
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mkdir CatPPT-exl2
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huggingface-cli download bartowski/CatPPT-exl2 --revision 8_0 --local-dir CatPPT-exl2 --local-dir-use-symlinks False
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```
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all_results.json
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{
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"epoch": 0.16,
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"eval_loss": 2.009287118911743,
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"eval_runtime": 16.1758,
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"eval_samples": 500,
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"eval_samples_per_second": 30.91,
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"eval_steps_per_second": 3.895,
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"train_loss": 2.0712431271870932,
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"train_runtime": 1041.0021,
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"train_samples": 9500,
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"train_samples_per_second": 9.126,
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"train_steps_per_second": 0.017
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}
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config.json
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{
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"_name_or_path": "rishiraj/CatPPT-base",
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"architectures": [
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"MistralForCausalLM"
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],
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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": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.36.1",
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"use_cache": true,
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"vocab_size": 32000
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}
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eval_results.json
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{
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"epoch": 0.16,
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"eval_loss": 2.009287118911743,
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"eval_runtime": 16.1758,
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"eval_samples": 500,
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"eval_samples_per_second": 30.91,
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"eval_steps_per_second": 3.895
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.36.1"
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}
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model.safetensors.index.json
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