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Update README.md

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  1. README.md +10 -10
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@@ -13,7 +13,7 @@ datasets:
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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><a href="https://discord.gg/UBgz4VXf">Chat & support: my new 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><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
@@ -78,7 +78,7 @@ Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](http
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  For further support, and discussions on these models and AI in general, join us at:
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- [TheBloke AI's Discord server](https://discord.gg/UBgz4VXf)
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  ## Thanks, and how to contribute.
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@@ -88,14 +88,14 @@ I've had a lot of people ask if they can contribute. I enjoy providing models an
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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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- 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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  * Patreon: https://patreon.com/TheBlokeAI
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  * Ko-Fi: https://ko-fi.com/TheBlokeAI
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- **Patreon special mentions**: Aemon Algiz; Dmitiry Samsonov; Jonathan Leane; Illia Dulskyi; Khalefa Al-Ahmad; Nikolai Manek; senxiiz; Talal Aujan; vamX; Eugene Pentland; Lone Striker; Luke Pendergrass; Johann-Peter Hartmann.
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- Thank you to all my generous patrons and donaters.
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  <!-- footer end -->
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  # Original model card: Chaoyi Wi's PMC_LLAMA 7B
@@ -104,8 +104,8 @@ This repo contains PMC_LLaMA_7B, which is LLaMA-7b finetuned on the PMC papers i
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  The model was trained with the following hyperparameters:
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- * Epochs: 5
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- * Batch size: 128
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  * Cutoff length: 512
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  * Learning rate: 2e-5
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@@ -118,13 +118,13 @@ import transformers
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  import torch
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  tokenizer = transformers.LlamaTokenizer.from_pretrained('chaoyi-wu/PMC_LLAMA_7B')
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  model = transformers.LlamaForCausalLM.from_pretrained('chaoyi-wu/PMC_LLAMA_7B')
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- sentence = 'Hello, doctor'
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  batch = tokenizer(
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  sentence,
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- return_tensors="pt",
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  add_special_tokens=False
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  )
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  with torch.no_grad():
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  generated = model.generate(inputs = batch["input_ids"], max_length=200, do_sample=True, top_k=50)
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  print('model predict: ',tokenizer.decode(generated[0]))
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- ```
 
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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><a href="https://discord.gg/Jq4vkcDakD">Chat & support: my new 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><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
 
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  For further support, and discussions on these models and AI in general, join us at:
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+ [TheBloke AI's Discord server](https://discord.gg/Jq4vkcDakD)
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  ## Thanks, and how to contribute.
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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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+ 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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  * Patreon: https://patreon.com/TheBlokeAI
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  * Ko-Fi: https://ko-fi.com/TheBlokeAI
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+ **Patreon special mentions**: Aemon Algiz, Dmitriy Samsonov, Nathan LeClaire, Trenton Dambrowitz, Mano Prime, David Flickinger, vamX, Nikolai Manek, senxiiz, Khalefa Al-Ahmad, Illia Dulskyi, Jonathan Leane, Talal Aujan, V. Lukas, Joseph William Delisle, Pyrater, Oscar Rangel, Lone Striker, Luke Pendergrass, Eugene Pentland, Sebastain Graf, Johann-Peter Hartman.
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+ Thank you to all my generous patrons and donaters!
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  <!-- footer end -->
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  # Original model card: Chaoyi Wi's PMC_LLAMA 7B
 
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  The model was trained with the following hyperparameters:
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+ * Epochs: 5
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+ * Batch size: 128
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  * Cutoff length: 512
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  * Learning rate: 2e-5
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  import torch
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  tokenizer = transformers.LlamaTokenizer.from_pretrained('chaoyi-wu/PMC_LLAMA_7B')
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  model = transformers.LlamaForCausalLM.from_pretrained('chaoyi-wu/PMC_LLAMA_7B')
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+ sentence = 'Hello, doctor'
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  batch = tokenizer(
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  sentence,
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+ return_tensors="pt",
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  add_special_tokens=False
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  )
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  with torch.no_grad():
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  generated = model.generate(inputs = batch["input_ids"], max_length=200, do_sample=True, top_k=50)
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  print('model predict: ',tokenizer.decode(generated[0]))
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+ ```