Update README.md

README.md

@@ -1,3 +1,83 @@
 ---
 license: apache-2.0
+language:
+- ru
+- en
+- de
+- es
+- it
+- ja
+- vi
+- zh
+- fr
+- pt
+- id
+- ko
+pipeline_tag: text-generation
 ---
+# 🌍 Vulture-40B
+***Vulture-40B*** is a further fine-tuned causal Decoder-only LLM built by Virtual Interactive (VILM), on top of the famous **Falcon-40B** by [TII](https://www.tii.ae). We collected a new dataset from news articles and Wikipedia's pages of **12 languages** (Total: **80GB**) and continue the pretraining process of Falcon-40B. Finally, we construct a multilingual instructional dataset following **Alpaca**'s techniques.
+
+While ***Vulture-40B*** is an adapter freely usable under **APACHE-2.0**, **Falcon-40B** itself remains available only under the **[Falcon-40B TII License](https://huggingface.co/spaces/tiiuae/falcon-40B-license/blob/main/LICENSE.txt) and [Acceptable Use Policy](https://huggingface.co/spaces/tiiuae/falcon-40B-license/blob/main/ACCEPTABLE_USE_POLICY.txt)**. Users should ensure any commercial applications based on ***Vulture-40B*** comply with the restrictions on **Falcon-40B**'s use.
+
+*Technical Report coming soon* 🤗
+
+## Prompt Format
+
+The reccomended model usage is:
+
+```
+A chat between a curious user and an artificial intelligence assistant.
+
+USER:{user's question}<|endoftext|>ASSISTANT:
+```
+
+# Model Details
+## Model Description
+- **Developed by:** [https://www.tii.ae](https://www.tii.ae);
+- **Finetuned by:** [Virtual Interactive](https://vilm.org);
+- **Language(s) (NLP):** English, German, Spanish, French, Portugese, Russian, Italian, Vietnamese, Indonesian, Chinese, Japanese and Chinese;
+- **Training Time:** 3,000 A100 Hours
+
+### Out-of-Scope Use
+
+Production use without adequate assessment of risks and mitigation; any use cases which may be considered irresponsible or harmful. 
+
+## Bias, Risks, and Limitations
+
+Vulture-40B is trained on a large-scale corpora representative of the web, it will carry the stereotypes and biases commonly encountered online.
+
+### Recommendations
+
+We recommend users of Vulture-40B to consider finetuning it for the specific set of tasks of interest, and for guardrails and appropriate precautions to be taken for any production use.
+
+## How to Get Started with the Model
+
+To run inference with the model in full `bfloat16` precision you need approximately 8xA100 80GB or equivalent.
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+from peft import PeftModel
+
+model = "tiiuae/falcon-40B"
+adapters_name = 'vilm/vulture-40B'
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+m = AutoModelForCausalLM.from_pretrained(model, torch_dtype=torch.bfloat16, device_map="auto" )
+m = PeftModel.from_pretrained(m, adapters_name)
+
+prompt = "A chat between a curious user and an artificial intelligence assistant.\n\nUSER:Thành phố Hồ Chí Minh nằm ở đâu?<|endoftext|>ASSISTANT:"
+
+inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+
+output = m.generate(input_ids=inputs["input_ids"],
+                    attention_mask=inputs["attention_mask"],
+                    do_sample=True,
+                    temperature=0.6,
+                    top_p=0.9,
+                    max_new_tokens=50,)
+output = output[0].to("cpu")
+print(tokenizer.decode(output))
+```