transformers safetensors falcon text-generation conversational custom_code dataset:allenai/c4 autotrain_compatible text-generation-inference endpoints_compatible 2-bit gptq region:us
---
datasets:
- allenai/c4
library_name: transformers
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->



## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This model is a quantized version of Falcon2-11B by [tiiuae](https://huggingface.co/tiiuae/falcon-11B). Quantization was performed with Auto-GPTQ to 2bit.

- **Developed by:** TIIIUAE
- **Quantised by:** Michael Svendsen

### Getting Started
```python
from transformers import AutoTokenizer, AutoModelForCausalLM, GPTQConfig

pretrained_model_name = "thesven/falcon-11B-GPTQ-2bit"
device = "cuda:0"

# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name)

# Load the model with the specified configuration and move to device
model = AutoModelForCausalLM.from_pretrained(
    pretrained_model_name,
    device_map="auto",
)
# Set EOS token ID
model.eos_token_id = tokenizer.eos_token_id

# Move model to the specified device
model.to(device)

# Define the input text
input_text = "Why is the sky blue?"

# Encode the input text
input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)

# Generate output
output = model.generate(input_ids, max_length=1000)

# Decode the generated output
decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True)

# Print the decoded output
for i, sequence in enumerate(decoded_output):
    print(f"Generated Sequence {i+1}: {sequence}")


```

## License
Falcon2-11B is licenced under [TII Falcon License 2.0(https://falconllm-staging.tii.ae/falcon-2-terms-and-conditions.html), the permissive Apache 2.0-based software license which includes an acceptable use policy that promotes the responsible use of AI.


## Uses
### Direct Use
Research on large language models; as a foundation for further specialization and finetuning for specific usecases (e.g., summarization, text generation, chatbot, etc.)

### 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
Falcon2-11B is trained mostly on English, but also German, Spanish, French, Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish. It will not generalize appropriately to other languages. Furthermore, as it 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 Falcon2-11B 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.