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Model: solidrust/Llama-3-8B-Instruct-DPO-v0.1-AWQ Source: Original Platform
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README.md
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---
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base_model: MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.1
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library_name: transformers
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tags:
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- 4-bit
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- AWQ
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- text-generation
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- autotrain_compatible
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- endpoints_compatible
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- axolotl
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- finetune
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- facebook
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- meta
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- pytorch
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- llama
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- llama-3
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language:
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- en
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pipeline_tag: text-generation
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license: other
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license_name: llama3
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license_link: LICENSE
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inference: false
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model_creator: MaziyarPanahi
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model_name: Llama-3-8B-Instruct-DPO-v0.1
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quantized_by: Suparious
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datasets:
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- mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha
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---
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# MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.1 AWQ
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- Model creator: [MaziyarPanahi](https://huggingface.co/MaziyarPanahi)
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- Original model: [Llama-3-8B-Instruct-DPO-v0.1](https://huggingface.co/MaziyarPanahi/Llama-3-8B-Instruct-DPO-v0.1)
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<img src="./llama-3-merges.webp" alt="Llama-3 DPO Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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This model is a fine-tune (DPO) of `meta-llama/Meta-Llama-3-8B-Instruct` model.
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## How to use
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This model uses `ChatML` prompt template:
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```
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<|im_start|>system
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{System}
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<|im_end|>
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<|im_start|>user
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{User}
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<|im_end|>
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<|im_start|>assistant
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{Assistant}
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````
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### Install the necessary packages
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```bash
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pip install --upgrade autoawq autoawq-kernels
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```
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### Example Python code
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```python
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from awq import AutoAWQForCausalLM
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from transformers import AutoTokenizer, TextStreamer
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model_path = "solidrust/Llama-3-8B-Instruct-DPO-v0.1-AWQ"
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system_message = "You are Llama-3-8B-Instruct-DPO-v0.1, incarnated as a powerful AI. You were created by MaziyarPanahi."
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# Load model
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model = AutoAWQForCausalLM.from_quantized(model_path,
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fuse_layers=True)
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tokenizer = AutoTokenizer.from_pretrained(model_path,
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trust_remote_code=True)
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streamer = TextStreamer(tokenizer,
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skip_prompt=True,
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skip_special_tokens=True)
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# Convert prompt to tokens
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prompt_template = """\
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<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant"""
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prompt = "You're standing on the surface of the Earth. "\
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"You walk one mile south, one mile west and one mile north. "\
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"You end up exactly where you started. Where are you?"
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tokens = tokenizer(prompt_template.format(system_message=system_message,prompt=prompt),
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return_tensors='pt').input_ids.cuda()
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# Generate output
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generation_output = model.generate(tokens,
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streamer=streamer,
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max_new_tokens=512)
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```
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### About AWQ
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AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.
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AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.
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It is supported by:
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- [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ
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- [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types.
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- [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference)
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- [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers
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- [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code
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config.json
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"max_position_embeddings": 8192,
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"model_type": "llama",
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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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"pretraining_tp": 1,
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"quantization_config": {
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"bits": 4,
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"group_size": 128,
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"modules_to_not_convert": null,
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"quant_method": "awq",
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"version": "gemm",
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"zero_point": true
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"rms_norm_eps": 1e-05,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.38.2",
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"use_cache": false,
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"vocab_size": 128257
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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}
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||||
6
quant_config.json
Normal file
6
quant_config.json
Normal file
@@ -0,0 +1,6 @@
|
||||
{
|
||||
"zero_point": true,
|
||||
"q_group_size": 128,
|
||||
"w_bit": 4,
|
||||
"version": "GEMM"
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
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|
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|
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|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3c32a921c5168d5106dba87588d8eb5049e0779cf046c0ba1d0f1d471f1d480c
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||||
size 9084650
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2071
tokenizer_config.json
Normal file
2071
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user