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+ ---
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+ base_model: openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf
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+ inference: false
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+ language:
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+ - th
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+ - en
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+ library_name: transformers
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+ license: apache-2.0
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+ model_creator: OpenThaiGPT
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+ model_name: OpenThaiGPT 1.0.0 Beta 13B Chat
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+ model_type: llama
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+ pipeline_tag: text-generation
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+ prompt_template: '[INST] <<SYS>>
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+
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+ {system_message}
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+
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+ <</SYS>>
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+
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+ {prompt} [/INST]
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+
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+ '
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+ quantized_by: TheBloke
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+ tags:
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+ - openthaigpt
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+ - llama
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+ ---
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+ <!-- markdownlint-disable MD041 -->
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+
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+ <!-- header start -->
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+ <!-- 200823 -->
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+ <div style="width: auto; margin-left: auto; margin-right: auto">
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+ <img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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+ </div>
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+ <div style="display: flex; justify-content: space-between; width: 100%;">
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+ <div style="display: flex; flex-direction: column; align-items: flex-start;">
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+ <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/theblokeai">Chat & support: TheBloke's Discord server</a></p>
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+ </div>
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+ <div style="display: flex; flex-direction: column; align-items: flex-end;">
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+ <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
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+ </div>
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+ </div>
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+ <div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">TheBloke's LLM work is generously supported by a grant from <a href="https://a16z.com">andreessen horowitz (a16z)</a></p></div>
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+ <hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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+ <!-- header end -->
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+
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+ # OpenThaiGPT 1.0.0 Beta 13B Chat - AWQ
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+ - Model creator: [OpenThaiGPT](https://huggingface.co/openthaigpt)
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+ - Original model: [OpenThaiGPT 1.0.0 Beta 13B Chat](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf)
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+
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+ <!-- description start -->
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+ ## Description
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+
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+ This repo contains AWQ model files for [OpenThaiGPT's OpenThaiGPT 1.0.0 Beta 13B Chat](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf).
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+
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+ These files were quantised using hardware kindly provided by [Massed Compute](https://massedcompute.com/).
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+
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+
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+ ### About AWQ
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+
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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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+
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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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+
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+ It is supported by:
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+
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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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+
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+ <!-- description end -->
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+ <!-- repositories-available start -->
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+ ## Repositories available
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+
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+ * [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/openthaigpt-1.0.0-beta-13B-chat-AWQ)
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+ * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/openthaigpt-1.0.0-beta-13B-chat-GPTQ)
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+ * [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/openthaigpt-1.0.0-beta-13B-chat-GGUF)
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+ * [OpenThaiGPT's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf)
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+ <!-- repositories-available end -->
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+
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+ <!-- prompt-template start -->
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+ ## Prompt template: Llama-2-Chat
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+
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+ ```
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+ [INST] <<SYS>>
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+ {system_message}
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+ <</SYS>>
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+ {prompt} [/INST]
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+
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+ ```
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+
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+ <!-- prompt-template end -->
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+ <!-- licensing start -->
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+ ## Licensing
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+
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+ The creator of the source model has listed its license as `apache-2.0`, and this quantization has therefore used that same license.
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+
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+ As this model is based on Llama 2, it is also subject to the Meta Llama 2 license terms, and the license files for that are additionally included. It should therefore be considered as being claimed to be licensed under both licenses. I contacted Hugging Face for clarification on dual licensing but they do not yet have an official position. Should this change, or should Meta provide any feedback on this situation, I will update this section accordingly.
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+
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+ In the meantime, any questions regarding licensing, and in particular how these two licenses might interact, should be directed to the original model repository: [OpenThaiGPT's OpenThaiGPT 1.0.0 Beta 13B Chat](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf).
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+ <!-- licensing end -->
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+ <!-- README_AWQ.md-provided-files start -->
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+ ## Provided files, and AWQ parameters
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+
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+ I currently release 128g GEMM models only. The addition of group_size 32 models, and GEMV kernel models, is being actively considered.
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+
108
+ Models are released as sharded safetensors files.
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+
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+ | Branch | Bits | GS | AWQ Dataset | Seq Len | Size |
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+ | ------ | ---- | -- | ----------- | ------- | ---- |
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+ | [main](https://huggingface.co/TheBloke/openthaigpt-1.0.0-beta-13B-chat-AWQ/tree/main) | 4 | 128 | [All Thai](https://huggingface.co/datasets/pbwt/all-thai/viewer/) | 4096 | 7.43 GB
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+
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+ <!-- README_AWQ.md-provided-files end -->
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+
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+ <!-- README_AWQ.md-text-generation-webui start -->
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+ ## How to easily download and use this model in [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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+
119
+ Please make sure you're using the latest version of [text-generation-webui](https://github.com/oobabooga/text-generation-webui).
120
+
121
+ It is strongly recommended to use the text-generation-webui one-click-installers unless you're sure you know how to make a manual install.
122
+
123
+ 1. Click the **Model tab**.
124
+ 2. Under **Download custom model or LoRA**, enter `TheBloke/openthaigpt-1.0.0-beta-13B-chat-AWQ`.
125
+ 3. Click **Download**.
126
+ 4. The model will start downloading. Once it's finished it will say "Done".
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+ 5. In the top left, click the refresh icon next to **Model**.
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+ 6. In the **Model** dropdown, choose the model you just downloaded: `openthaigpt-1.0.0-beta-13B-chat-AWQ`
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+ 7. Select **Loader: AutoAWQ**.
130
+ 8. Click Load, and the model will load and is now ready for use.
131
+ 9. If you want any custom settings, set them and then click **Save settings for this model** followed by **Reload the Model** in the top right.
132
+ 10. Once you're ready, click the **Text Generation** tab and enter a prompt to get started!
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+ <!-- README_AWQ.md-text-generation-webui end -->
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+
135
+ <!-- README_AWQ.md-use-from-vllm start -->
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+ ## Multi-user inference server: vLLM
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+
138
+ Documentation on installing and using vLLM [can be found here](https://vllm.readthedocs.io/en/latest/).
139
+
140
+ - Please ensure you are using vLLM version 0.2 or later.
141
+ - When using vLLM as a server, pass the `--quantization awq` parameter.
142
+
143
+ For example:
144
+
145
+ ```shell
146
+ python3 -m vllm.entrypoints.api_server --model TheBloke/openthaigpt-1.0.0-beta-13B-chat-AWQ --quantization awq --dtype auto
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+ ```
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+
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+ - When using vLLM from Python code, again set `quantization=awq`.
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+
151
+ For example:
152
+
153
+ ```python
154
+ from vllm import LLM, SamplingParams
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+
156
+ prompts = [
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+ "Tell me about AI",
158
+ "Write a story about llamas",
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+ "What is 291 - 150?",
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+ "How much wood would a woodchuck chuck if a woodchuck could chuck wood?",
161
+ ]
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+ prompt_template=f'''[INST] <<SYS>>
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+ {system_message}
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+ <</SYS>>
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+ {prompt} [/INST]
166
+ '''
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+
168
+ prompts = [prompt_template.format(prompt=prompt) for prompt in prompts]
169
+
170
+ sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
171
+
172
+ llm = LLM(model="TheBloke/openthaigpt-1.0.0-beta-13B-chat-AWQ", quantization="awq", dtype="auto")
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+
174
+ outputs = llm.generate(prompts, sampling_params)
175
+
176
+ # Print the outputs.
177
+ for output in outputs:
178
+ prompt = output.prompt
179
+ generated_text = output.outputs[0].text
180
+ print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
181
+ ```
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+ <!-- README_AWQ.md-use-from-vllm start -->
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+
184
+ <!-- README_AWQ.md-use-from-tgi start -->
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+ ## Multi-user inference server: Hugging Face Text Generation Inference (TGI)
186
+
187
+ Use TGI version 1.1.0 or later. The official Docker container is: `ghcr.io/huggingface/text-generation-inference:1.1.0`
188
+
189
+ Example Docker parameters:
190
+
191
+ ```shell
192
+ --model-id TheBloke/openthaigpt-1.0.0-beta-13B-chat-AWQ --port 3000 --quantize awq --max-input-length 3696 --max-total-tokens 4096 --max-batch-prefill-tokens 4096
193
+ ```
194
+
195
+ Example Python code for interfacing with TGI (requires [huggingface-hub](https://github.com/huggingface/huggingface_hub) 0.17.0 or later):
196
+
197
+ ```shell
198
+ pip3 install huggingface-hub
199
+ ```
200
+
201
+ ```python
202
+ from huggingface_hub import InferenceClient
203
+
204
+ endpoint_url = "https://your-endpoint-url-here"
205
+
206
+ prompt = "Tell me about AI"
207
+ prompt_template=f'''[INST] <<SYS>>
208
+ {system_message}
209
+ <</SYS>>
210
+ {prompt} [/INST]
211
+ '''
212
+
213
+ client = InferenceClient(endpoint_url)
214
+ response = client.text_generation(prompt,
215
+ max_new_tokens=128,
216
+ do_sample=True,
217
+ temperature=0.7,
218
+ top_p=0.95,
219
+ top_k=40,
220
+ repetition_penalty=1.1)
221
+
222
+ print(f"Model output: ", response)
223
+ ```
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+ <!-- README_AWQ.md-use-from-tgi end -->
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+
226
+ <!-- README_AWQ.md-use-from-python start -->
227
+ ## Inference from Python code using Transformers
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+
229
+ ### Install the necessary packages
230
+
231
+ - Requires: [Transformers](https://huggingface.co/docs/transformers) 4.35.0 or later.
232
+ - Requires: [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) 0.1.6 or later.
233
+
234
+ ```shell
235
+ pip3 install --upgrade "autoawq>=0.1.6" "transformers>=4.35.0"
236
+ ```
237
+
238
+ Note that if you are using PyTorch 2.0.1, the above AutoAWQ command will automatically upgrade you to PyTorch 2.1.0.
239
+
240
+ If you are using CUDA 11.8 and wish to continue using PyTorch 2.0.1, instead run this command:
241
+
242
+ ```shell
243
+ pip3 install https://github.com/casper-hansen/AutoAWQ/releases/download/v0.1.6/autoawq-0.1.6+cu118-cp310-cp310-linux_x86_64.whl
244
+ ```
245
+
246
+ If you have problems installing [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) using the pre-built wheels, install it from source instead:
247
+
248
+ ```shell
249
+ pip3 uninstall -y autoawq
250
+ git clone https://github.com/casper-hansen/AutoAWQ
251
+ cd AutoAWQ
252
+ pip3 install .
253
+ ```
254
+
255
+ ### Transformers example code (requires Transformers 4.35.0 and later)
256
+
257
+ ```python
258
+ from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
259
+
260
+ model_name_or_path = "TheBloke/openthaigpt-1.0.0-beta-13B-chat-AWQ"
261
+
262
+ tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
263
+ model = AutoModelForCausalLM.from_pretrained(
264
+ model_name_or_path,
265
+ low_cpu_mem_usage=True,
266
+ device_map="cuda:0"
267
+ )
268
+
269
+ # Using the text streamer to stream output one token at a time
270
+ streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
271
+
272
+ prompt = "Tell me about AI"
273
+ prompt_template=f'''[INST] <<SYS>>
274
+ {system_message}
275
+ <</SYS>>
276
+ {prompt} [/INST]
277
+ '''
278
+
279
+ # Convert prompt to tokens
280
+ tokens = tokenizer(
281
+ prompt_template,
282
+ return_tensors='pt'
283
+ ).input_ids.cuda()
284
+
285
+ generation_params = {
286
+ "do_sample": True,
287
+ "temperature": 0.7,
288
+ "top_p": 0.95,
289
+ "top_k": 40,
290
+ "max_new_tokens": 512,
291
+ "repetition_penalty": 1.1
292
+ }
293
+
294
+ # Generate streamed output, visible one token at a time
295
+ generation_output = model.generate(
296
+ tokens,
297
+ streamer=streamer,
298
+ **generation_params
299
+ )
300
+
301
+ # Generation without a streamer, which will include the prompt in the output
302
+ generation_output = model.generate(
303
+ tokens,
304
+ **generation_params
305
+ )
306
+
307
+ # Get the tokens from the output, decode them, print them
308
+ token_output = generation_output[0]
309
+ text_output = tokenizer.decode(token_output)
310
+ print("model.generate output: ", text_output)
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+
312
+ # Inference is also possible via Transformers' pipeline
313
+ from transformers import pipeline
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+
315
+ pipe = pipeline(
316
+ "text-generation",
317
+ model=model,
318
+ tokenizer=tokenizer,
319
+ **generation_params
320
+ )
321
+
322
+ pipe_output = pipe(prompt_template)[0]['generated_text']
323
+ print("pipeline output: ", pipe_output)
324
+
325
+ ```
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+ <!-- README_AWQ.md-use-from-python end -->
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+
328
+ <!-- README_AWQ.md-compatibility start -->
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+ ## Compatibility
330
+
331
+ The files provided are tested to work with:
332
+
333
+ - [text-generation-webui](https://github.com/oobabooga/text-generation-webui) using `Loader: AutoAWQ`.
334
+ - [vLLM](https://github.com/vllm-project/vllm) version 0.2.0 and later.
335
+ - [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference) version 1.1.0 and later.
336
+ - [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later.
337
+ - [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) version 0.1.1 and later.
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+
339
+ <!-- README_AWQ.md-compatibility end -->
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+
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+ <!-- footer start -->
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+ <!-- 200823 -->
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+ ## Discord
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+
345
+ For further support, and discussions on these models and AI in general, join us at:
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+
347
+ [TheBloke AI's Discord server](https://discord.gg/theblokeai)
348
+
349
+ ## Thanks, and how to contribute
350
+
351
+ Thanks to the [chirper.ai](https://chirper.ai) team!
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+
353
+ Thanks to Clay from [gpus.llm-utils.org](llm-utils)!
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+
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+ I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
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+
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+ If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
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+
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+ Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.
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+
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+ * Patreon: https://patreon.com/TheBlokeAI
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+ * Ko-Fi: https://ko-fi.com/TheBlokeAI
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+
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+ **Special thanks to**: Aemon Algiz.
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+
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+ **Patreon special mentions**: Michael Levine, 阿明, Trailburnt, Nikolai Manek, John Detwiler, Randy H, Will Dee, Sebastain Graf, NimbleBox.ai, Eugene Pentland, Emad Mostaque, Ai Maven, Jim Angel, Jeff Scroggin, Michael Davis, Manuel Alberto Morcote, Stephen Murray, Robert, Justin Joy, Luke @flexchar, Brandon Frisco, Elijah Stavena, S_X, Dan Guido, Undi ., Komninos Chatzipapas, Shadi, theTransient, Lone Striker, Raven Klaugh, jjj, Cap'n Zoog, Michel-Marie MAUDET (LINAGORA), Matthew Berman, David, Fen Risland, Omer Bin Jawed, Luke Pendergrass, Kalila, OG, Erik Bjäreholt, Rooh Singh, Joseph William Delisle, Dan Lewis, TL, John Villwock, AzureBlack, Brad, Pedro Madruga, Caitlyn Gatomon, K, jinyuan sun, Mano Prime, Alex, Jeffrey Morgan, Alicia Loh, Illia Dulskyi, Chadd, transmissions 11, fincy, Rainer Wilmers, ReadyPlayerEmma, knownsqashed, Mandus, biorpg, Deo Leter, Brandon Phillips, SuperWojo, Sean Connelly, Iucharbius, Jack West, Harry Royden McLaughlin, Nicholas, terasurfer, Vitor Caleffi, Duane Dunston, Johann-Peter Hartmann, David Ziegler, Olakabola, Ken Nordquist, Trenton Dambrowitz, Tom X Nguyen, Vadim, Ajan Kanaga, Leonard Tan, Clay Pascal, Alexandros Triantafyllidis, JM33133, Xule, vamX, ya boyyy, subjectnull, Talal Aujan, Alps Aficionado, wassieverse, Ari Malik, James Bentley, Woland, Spencer Kim, Michael Dempsey, Fred von Graf, Elle, zynix, William Richards, Stanislav Ovsiannikov, Edmond Seymore, Jonathan Leane, Martin Kemka, usrbinkat, Enrico Ros
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+
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+
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+ Thank you to all my generous patrons and donaters!
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+
371
+ And thank you again to a16z for their generous grant.
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+
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+ <!-- footer end -->
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+
375
+ # Original model card: OpenThaiGPT's OpenThaiGPT 1.0.0 Beta 13B Chat
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+
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+
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+ # 🇹🇭 OpenThaiGPT 13b 1.0.0-beta Chat with 16 bits in Huggingface's format.
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+ <img src="https://1173516064-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FvvbWvIIe82Iv1yHaDBC5%2Fuploads%2Fb8eiMDaqiEQL6ahbAY0h%2Fimage.png?alt=media&token=6fce78fd-2cca-4c0a-9648-bd5518e644ce
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+ https://openthaigpt.aieat.or.th/" width="200px">
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+
382
+ 🇹🇭 OpenThaiGPT 13b Version 1.0.0-beta is a Thai language 13B-parameter LLaMA v2 Chat model finetuned to follow Thai translated instructions and extend more than 10,000 most popular Thai words vocabularies into LLM's dictionary for turbo speed.
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+
384
+ ## Licenses
385
+ **Source Code**: License Apache Software License 2.0.<br>
386
+ **Weight**: Research and **Commercial uses**.<br>
387
+
388
+ ## Codes and Weight
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+ **Finetune Code**: https://github.com/OpenThaiGPT/openthaigpt-finetune-010beta<br>
390
+ **Inference Code**: https://github.com/OpenThaiGPT/openthaigpt<br>
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+ **Weight (Huggingface Checkpoint)**: https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf
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+
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+ ## Sponsors
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/5fcd9c426d942eaf4d1ebd30/42d-GioSs4evIdNuMAaPB.png" width="600px">
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+
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+ ## Supports
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+ - Official website: https://openthaigpt.aieat.or.th
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+ - Facebook page: https://web.facebook.com/groups/openthaigpt
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+ - A Discord server for discussion and support [here](https://discord.gg/rUTp6dfVUF)
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+ - E-mail: [email protected]
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+
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+ ## Description
403
+ Prompt format is Llama2
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+ ```
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+ <s>[INST] <<SYS>>
406
+ system_prompt
407
+ <</SYS>>
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+
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+ question [/INST]
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+ ```
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+ System prompt:
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+ You are a question answering assistant. Answer the question as truthful and helpful as possible คุณคือผู้ช่วยตอบคำถาม จงตอบคำถามอย่างถูกต้องและมีประโยชน์ที่สุด
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+
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+ ## How to use
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+
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+ 1. install VLLM (https://github.com/vllm-project/vllm)
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+ 2. python -m vllm.entrypoints.api_server --model /path/to/model --tensor-parallel-size num_gpus
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+ 3. run inference (CURL example)
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+
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+ ```
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+ curl --request POST \
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+ --url http://localhost:8000/generate \
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+ --header "Content-Type: application/json" \
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+ --data '{"prompt": "<s>[INST] <<SYS>>\nYou are a question answering assistant. Answer the question as truthful and helpful as possible คุณคือผู้ช่วยตอบคำถาม จงตอบคำถามอย่างถูกต้องและมีประโยชน์ที่สุด\n<</SYS>>\n\nอยากลดความอ้วนต้องทำอย่างไร [/INST]","use_beam_search": false, "temperature": 0.1, "max_tokens": 512, "top_p": 0.75, "top_k": 40, "frequency_penalty": 0.3 "stop": "</s>"}'
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+ ```
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+
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+ ### Authors
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+ * Kobkrit Viriyayudhakorn ([email protected])
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+ * Sumeth Yuenyong ([email protected])
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+ * Thaweewat Rugsujarit ([email protected])
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+ * Jillaphat Jaroenkantasima ([email protected])
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+ * Norapat Buppodom ([email protected])
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+ * Koravich Sangkaew ([email protected])
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+ * Peerawat Rojratchadakorn ([email protected])
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+ * Surapon Nonesung ([email protected])
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+ * Chanon Utupon ([email protected])
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+ * Sadhis Wongprayoon ([email protected])
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+ * Nucharee Thongthungwong ([email protected])
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+ * Chawakorn Phiantham ([email protected])
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+ * Patteera Triamamornwooth ([email protected])
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+ * Nattarika Juntarapaoraya ([email protected])
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+ * Kriangkrai Saetan ([email protected])
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+ * Pitikorn Khlaisamniang ([email protected])
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+
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+ <i>Disclaimer: Provided responses are not guaranteed.</i>