Mohammed-Altaf
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Upload 10 files
Browse files- .gitattributes +0 -1
- README.md +48 -1
- added_tokens.json +3 -0
- config.json +39 -0
- generation_config.json +7 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +18 -0
- tokenizer_config.json +34 -0
- vocab.json +0 -0
.gitattributes
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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*.wasm filter=lfs diff=lfs merge=lfs -text
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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-
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---
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---
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tags:
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- medical
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---
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Please note that the chatbot is designed for research purposes only and is not intended for use in real medical settings. While the chatbot has been trained to provide accurate and helpful responses, it is not a substitute for professional medical advice, diagnosis, or treatment. The information provided by the chatbot should not be used to make medical decisions, and any health concerns should be addressed by a licensed healthcare provider.
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## Quickstart
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```python
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import torch
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from transformers import GPT2LMHeadModel, GPT2Tokenizer
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path = "jianghc/medical_chatbot"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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tokenizer = GPT2Tokenizer.from_pretrained(path)
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model = GPT2LMHeadModel.from_pretrained(path).to(device)
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prompt_input = (
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"The conversation between human and AI assistant.\n"
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"[|Human|] {input}\n"
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"[|AI|]"
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)
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sentence = prompt_input.format_map({'input': "what is parkinson's disease?"})
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inputs = tokenizer(sentence, return_tensors="pt").to(device)
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with torch.no_grad():
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beam_output = model.generate(**inputs,
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min_new_tokens=1,
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max_length=512,
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num_beams=3,
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repetition_penalty=1.2,
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early_stopping=True,
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eos_token_id=198
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)
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print(tokenizer.decode(beam_output[0], skip_special_tokens=True))
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```
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## Example Outputs
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```
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The conversation between human and AI assistant.
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[|Human|] what is parkinson's disease?
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[|AI|] Parkinson's disease is a neurodegenerative disorder that affects movement. It is caused by the loss of dopamine-producing cells in the brain.
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```
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```
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The conversation between human and AI assistant.
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[|Human|] what type of honey is best for a bad covid cough?
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[|AI|] Manuka honey has been shown to have anti-inflammatory and antibacterial properties that can help alleviate symptoms of a bad covid cough.
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```
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added_tokens.json
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{
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"[PAD]": 28895
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}
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config.json
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{
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"_name_or_path": "biomedLM_baize/checkpoint-1000",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 28895,
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"embd_pdrop": 0.1,
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"eos_token_id": 28895,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 2560,
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"n_head": 20,
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"n_inner": null,
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"n_layer": 32,
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"n_positions": 1024,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": true,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.26.1",
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"use_cache": false,
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"vocab_size": 28896
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 28895,
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"eos_token_id": 28895,
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"transformers_version": "4.26.1",
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"use_cache": false
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}
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merges.txt
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:2cac4bd8d32e7fce74c7cc3dc5bba17fefa7c26942f36916557ee9a3a3d7f0ba
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size 10410689701
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": "[PAD]",
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"pad_token": "[PAD]",
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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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_config.json
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{
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"add_bos_token": false,
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"add_prefix_space": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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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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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"errors": "replace",
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"model_max_length": 1024,
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"name_or_path": "biomedLM_baize/checkpoint-1000",
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"pad_token": null,
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"special_tokens_map_file": null,
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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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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vocab.json
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