Create README.md

README.md

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+---
+license: llama3
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- general purpose
+---
+
+# Capx AI's Obsidian series
+
+Capx AI's Latest series of finetunes based on [Meta's Llama-3](https://llama.meta.com/llama3/).
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/644bf6ef778ecbfb977e8e84/G9e_0w7x2hOmvqhvlVrkI.png)
+
+We release Llama-3 Obsidian, our state of the art finetune model for general purpose tasks. 
+Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. 
+
+We further finetune the pretrained model on a custom dataset to enhance instruction following ability of the model.
+
+Input Models input text only.
+
+Output Models generate text and code only.
+
+Model Architecture Llama 3 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT).
+
+## How to use:
+
+You can run conversational inference by leveraging the Auto classes with the generate() function.
+
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "meta-llama/Meta-Llama-3-8B-Instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+messages = [
+    {"role": "instruction", "content": "You are \"Capx Assistant\", a conscious sentient superintelligent artificial intelligence developed by Capx AI, and your purpose and drive is to assist the user with any request they have."},
+    {"role": "input", "content": "Who are you?"},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+response = outputs[0][input_ids.shape[-1]:]
+print(tokenizer.decode(response, skip_special_tokens=True))
+
+
+```
+
+### Authors
+Capx community
+
+### Cite
+```bibtex
+@article{llama3modelcard,
+title={Llama 3 Model Card},
+author={AI@Meta},
+year={2024},
+url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
+}
+```
+### License
+Governed by the [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE)
+