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Duplicate from anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g

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Co-authored-by: z. <anon8231489123@users.noreply.huggingface.co>

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README.md ADDED
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+ ---
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+ duplicated_from: anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g
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+ ---
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+
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+ Update (4/1): Added ggml for Cuda model
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+
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+ Dataset is here (instruct): https://github.com/teknium1/GPTeacher
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+
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+ Okay... Two different models now. One generated in the Triton branch, one generated in Cuda. Use the Cuda one for now unless the Triton branch becomes widely used.
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+
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+ Cuda info (use this one):
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+ Command:
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+
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+ CUDA_VISIBLE_DEVICES=0 python llama.py ./models/chavinlo-gpt4-x-alpaca --wbits 4 --true-sequential --groupsize 128 --save gpt-x-alpaca-13b-native-4bit-128g-cuda.pt
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+
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+
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+ Prev. info
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+
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+ Quantized on GPTQ-for-LLaMa commit 5955e9c67d9bfe8a8144ffbe853c2769f1e87cdd
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+
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+ GPTQ 4bit quantization of: https://huggingface.co/chavinlo/gpt4-x-alpaca
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+
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+ Note: This was quantized with this branch of GPTQ-for-LLaMA: https://github.com/qwopqwop200/GPTQ-for-LLaMa/tree/triton
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+
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+ Because of this, it appears to be incompatible with Oobabooga at the moment. Stay tuned?
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+
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+ Command:
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+
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+ CUDA_VISIBLE_DEVICES=0 python llama.py ./models/chavinlo-gpt4-x-alpaca --wbits 4 --true-sequential --act-order --groupsize 128 --save gpt-x-alpaca-13b-native-4bit-128g.pt
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+ {
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+ "_name_or_path": "./output",
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+ "architectures": [
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+ "LLaMAForCausalLM"
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+ ],
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+ "bos_token_id": 0,
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+ "eos_token_id": 1,
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+ "hidden_act": "silu",
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+ "hidden_size": 5120,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 13824,
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+ "max_sequence_length": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 40,
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+ "num_hidden_layers": 40,
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+ "pad_token_id": -1,
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+ "rms_norm_eps": 1e-06,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.27.0.dev0",
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+ "use_cache": true,
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+ "vocab_size": 32001
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+ }
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+ }
ggml_README.txt ADDED
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+ The model is for: https://github.com/ggerganov/llama.cpp
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+
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+ Date: 2023-04-01
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+ ggml model file magic: 0x67676a74 (ggjt in hex)
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+ ggml model file version: 1
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+
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+ Torrent contents:
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+ The fine tune described at https://huggingface.co/chavinlo/gpt4-x-alpaca converted to ggml format from https://huggingface.co/anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g/blob/f267949dcd5a5e6451933cec3d0b5661f4f9c889/gpt-x-alpaca-13b-native-4bit-128g-cuda.pt
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+ Details about the GPTQ quantization process: https://huggingface.co/anon8231489123/gpt4-x-alpaca-13b-native-4bit-128g/blob/f267949dcd5a5e6451933cec3d0b5661f4f9c889/README.md
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+
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+ Tools used:
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+ [1] Conversion to ggml: https://github.com/ggerganov/llama.cpp/blob/3265b102beb7674d010644ca2a1bd30a58f9f6b5/convert.py and [2]
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+ [2] Added extra tokens: https://huggingface.co/chavinlo/alpaca-13b/blob/464a0bd1ec16f3a7d5295a0035aff87f307e62f1/added_tokens.json
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+ [3] Migration to the latest llama.cpp model format: https://github.com/ggerganov/llama.cpp/blob/3525899277d2e2bdc8ec3f0e6e40c47251608700/migrate-ggml-2023-03-30-pr613.py
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