Update README.md

README.md

@@ -1,3 +1,83 @@
 ---
 license: apache-2.0
 ---
+### BioinspiredZephyr-7B: Large Language Model for the Mechanics of Biological and Bio-Inspired Materials using Mixture-of-Experts
+
+To accelerate discovery and guide insights, we report an open-source autoregressive transformer large language model (LLM), trained on expert knowledge in the biological materials field, especially focused on mechanics and structural properties.
+
+The model is finetuned with a corpus of over a thousand peer-reviewed articles in the field of structural biological and bio-inspired materials and can be prompted to recall information, assist with research tasks, and function as an engine for creativity.
+
+The model is based on HuggingFaceH4/zephyr-7b-beta.
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/623ce1c6b66fedf374859fe7/bsqBByauWBZ0Y8PspthR8.png)
+
+This model is based on work reported in https://doi.org/10.1002/advs.202306724.
+
+This repository includes both, Hugging Face transformers and GGUF files (in different versions, the q5_K_M is recommended). 
+
+```
+from llama_cpp import Llama
+
+model_path='./BioinspiredZephyr-7B/ggml-model-q5_K_M.gguf'
+chat_format="mistral-instruct"
+
+llm = Llama(model_path=model_path,
+            n_gpu_layers=-1,verbose= True, 
+            n_ctx=10000,
+            #main_gpu=0,
+            chat_format=chat_format,
+            #split_mode=llama_cpp.LLAMA_SPLIT_LAYER
+            )
+```
+
+Or, download directly from Hugging Face:
+
+```
+from llama_cpp import Llama
+
+model_path='lamm-mit/BioinspiredZephyr-7B/ggml-model-q5_K_M.gguf'
+chat_format="mistral-instruct"
+
+llm = Llama.from_pretrained(
+    repo_id=model_path,
+    filename="*q5_K_M.gguf",
+    verbose=True,
+    n_gpu_layers=-1, 
+    n_ctx=10000,
+    #main_gpu=0,
+    chat_format=chat_format,
+)
+```
+For inference:
+```
+def generate_BioinspiredZephyr_7B(system_prompt='You are an expert in biological materials, mechanics and related topics.',
+                                  prompt="What is spider silk?",
+                                  temperature=0.0,
+                                  max_tokens=10000,  
+                                  ):
+    if system_prompt==None:
+        messages=[
+            {"role": "user", "content": prompt},
+            ]
+    else:
+        messages=[
+            {"role": "system",  "content": system_prompt},
+            {"role": "user", "content": prompt},
+        ]
+
+    result=llm.create_chat_completion(
+            messages=messages,
+            temperature=temperature,
+            max_tokens=max_tokens,
+        )
+
+start_time = time.time()
+result=generate_BioinspiredZephyr_7B(system_prompt='You respond accurately.', 
+                        prompt="What is graphene? Answer with detail.",
+                        max_tokens=512, temperature=0.7,  )
+print (result)
+deltat=time.time() - start_time
+print("--- %s seconds ---" % deltat)
+toked=tokenizer(res)
+print ("Tokens per second (generation): ", len (toked['input_ids'])/deltat)
+```