Instructions to use gouthamsai78/myai-awesome-prompts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gouthamsai78/myai-awesome-prompts with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "gouthamsai78/myai-awesome-prompts") - Transformers
How to use gouthamsai78/myai-awesome-prompts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="gouthamsai78/myai-awesome-prompts") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("gouthamsai78/myai-awesome-prompts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use gouthamsai78/myai-awesome-prompts with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gouthamsai78/myai-awesome-prompts" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gouthamsai78/myai-awesome-prompts", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/gouthamsai78/myai-awesome-prompts
- SGLang
How to use gouthamsai78/myai-awesome-prompts with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "gouthamsai78/myai-awesome-prompts" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gouthamsai78/myai-awesome-prompts", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "gouthamsai78/myai-awesome-prompts" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gouthamsai78/myai-awesome-prompts", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use gouthamsai78/myai-awesome-prompts with Docker Model Runner:
docker model run hf.co/gouthamsai78/myai-awesome-prompts
Fine-tuned on awesome-chatgpt-prompts
Browse files- README.md +57 -0
- chat_template.jinja +24 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +44 -0
README.md
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---
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library_name: peft
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license: apache-2.0
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base_model: mistralai/Mistral-7B-Instruct-v0.2
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tags:
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- base_model:adapter:mistralai/Mistral-7B-Instruct-v0.2
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- lora
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- transformers
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pipeline_tag: text-generation
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model-index:
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- name: myai-awesome-prompts
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# myai-awesome-prompts
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 1
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### Training results
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### Framework versions
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- PEFT 0.17.0
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- Transformers 4.56.0.dev0
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- Pytorch 2.6.0+cu124
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- Datasets 4.0.0
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- Tokenizers 0.21.4
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chat_template.jinja
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content'] %}
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{%- set loop_messages = messages[1:] %}
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{%- else %}
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{%- set loop_messages = messages %}
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{%- endif %}
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{{- bos_token }}
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{%- for message in loop_messages %}
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{%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}
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{{- raise_exception('After the optional system message, conversation roles must alternate user/assistant/user/assistant/...') }}
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{%- endif %}
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{%- if message['role'] == 'user' %}
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{%- if loop.first and system_message is defined %}
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{{- ' [INST] ' + system_message + '\n\n' + message['content'] + ' [/INST]' }}
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{%- else %}
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{{- ' [INST] ' + message['content'] + ' [/INST]' }}
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{%- endif %}
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{%- elif message['role'] == 'assistant' %}
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{{- ' ' + message['content'] + eos_token}}
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{%- else %}
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{{- raise_exception('Only user and assistant roles are supported, with the exception of an initial optional system message!') }}
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{%- endif %}
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{%- endfor %}
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "</s>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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See raw diff
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"add_prefix_space": null,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [],
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"extra_special_tokens": {},
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"legacy": false,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "</s>",
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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