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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - finetuned
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+ - quantized
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+ - 4-bit
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+ - gptq
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+ - transformers
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+ - pytorch
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+ - safetensors
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+ - mistral
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+ - text-generation
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+ - generated_from_trainer
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+ - en
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+ - dataset:HuggingFaceH4/ultrachat_200k
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+ - dataset:HuggingFaceH4/ultrafeedback_binarized
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+ - arxiv:2305.18290
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+ - arxiv:2310.16944
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+ - base_model:mistralai/Mistral-7B-v0.1
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+ - license:mit
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+ - model-index
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+ - autotrain_compatible
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+ - endpoints_compatible
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+ - has_space
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+ - text-generation-inference
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+ - region:us
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+ model_name: zephyr-7b-beta-GPTQ
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+ base_model: HuggingFaceH4/zephyr-7b-beta
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+ inference: false
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+ model_creator: HuggingFaceH4
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+ pipeline_tag: text-generation
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+ quantized_by: MaziyarPanahi
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+ ---
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+ # Description
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+ [MaziyarPanahi/zephyr-7b-beta-GPTQ](https://huggingface.co/MaziyarPanahi/zephyr-7b-beta-GPTQ) is a quantized (GPTQ) version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)
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+
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+ ## How to use
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+ ### Install the necessary packages
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+
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+ ```
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+ pip install --upgrade accelerate auto-gptq transformers
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+ ```
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+
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+ ### Example Python code
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+
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+
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+ ```python
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+ from transformers import AutoTokenizer, pipeline
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+ from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
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+ import torch
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+
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+ model_id = "MaziyarPanahi/zephyr-7b-beta-GPTQ"
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+
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+ quantize_config = BaseQuantizeConfig(
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+ bits=4,
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+ group_size=128,
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+ desc_act=False
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+ )
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+
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+ model = AutoGPTQForCausalLM.from_quantized(
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+ model_id,
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+ use_safetensors=True,
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+ device="cuda:0",
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+ quantize_config=quantize_config)
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_id)
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+
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+ pipe = pipeline(
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+ "text-generation",
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+ model=model,
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+ tokenizer=tokenizer,
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+ max_new_tokens=512,
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+ temperature=0.7,
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+ top_p=0.95,
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+ repetition_penalty=1.1
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+ )
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+
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+ outputs = pipe("What is a large language model?")
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+ print(outputs[0]["generated_text"])
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "HuggingFaceH4/zephyr-7b-beta",
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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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+ "pad_token_id": 2,
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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": "float16",
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+ "transformers_version": "4.36.2",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
model.safetensors ADDED
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quantize_config.json ADDED
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+ {
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+ "bits": 4,
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+ "damp_percent": 0.1,
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+ "desc_act": false,
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+ "static_groups": false,
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+ "sym": true,
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+ "true_sequential": true,
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+ "model_name_or_path": null,
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+ "model_file_base_name": null
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+ }
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+ {
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tokenizer.json ADDED
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+ {
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+ "add_bos_token": true,
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+ "added_tokens_decoder": {
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+ "bos_token": "<s>",
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+ "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
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+ }